BEFORE
Unoptimized
5 stages · 9.4 GB
Artificial Intelligence ready for production
The AI agents your
business needs,
without paying for the AI
We build your system with integrated artificial intelligence. You pay for the development. The AI is included.
57+
Agents available
0.29%
Hallucination rate
18+
Connected systems
The model that changes everything
A contract management
system with AI.
We don't charge you for the AI.
Every mid-sized or large company has active contracts that nobody manages well. They sit in folders, in unlabeled emails, in SharePoint with no order. Nobody knows when they expire, what penalties they carry, or which clauses expose the company.
The cost is not invisible: contracts that auto-renew because no one checked the date, vendors raising prices with no one catching it, penalties paid because the clause was on page 47.
We build the system that reads, understands, and monitors all your contracts. You pay for the development. The AI — extractors, alerts, clause analysis — is included.
"How many active contracts do you have right now? Do you know when each one expires? Who in your company has read them all?"
If the answer makes you uncomfortable, you've found the problem. We have the solution — and we don't charge you for the AI.
If the answer makes you uncomfortable, you've found the problem. We have the solution — and we don't charge you for the AI.
1
The system reads and interprets all your contracts automatically
2
Extracts expiration dates, penalties, parties, and critical clauses
3
Alerts you 90 days before each expiration, automatically
4
You pay for the system development. The contracts AI already exists.
Why architecture matters
AI extracts.
A formal engine decides.
Most agents on the market delegate everything to the LLM: reasoning, decision-making, and action. MIKA doesn't. Here's why that matters when errors have real consequences.
LLM-centric Agent
The LLM reasons, decides, and acts
ChatGPT, Copilot, generic agents
Non-deterministic responses
The same invoice processed twice can yield different results. At temperature 0, the LLM does not guarantee consistency.
Hallucinations with no safety net
The LLM can fabricate an amount, a date, or a clause that doesn't exist in the document. Without cross-verification, no one catches it.
Black box — not auditable
«Why did the agent make that decision?» There's no answer. The logic is implicit in the model's weights and is not inspectable.
No formal guarantees
It's impossible to certify that the system will always behave within defined limits. Meeting GDPR, DORA, or ISO 27001 on a non-deterministic base is unachievable.
Prompt-sensitive
A change in how the prompt is worded can alter the system's behavior in production. Fragile by nature.
VS
MIKA Architecture
The LLM extracts. The engine decides.
BDI-HTN Engine + LLM as typed sensor
Deterministic extraction
The LLM operates at temperature=0 with a forced JSON Schema. It only extracts typed data anchored to the original document. No free interpretation.
VERA cross-verification
Each extracted field is anchored to its exact position in the document. If the data can't be confirmed, it declares it — never invents it. Hallucination rate: 0.29%.
Formal, auditable decisions
The BDI-HTN engine makes all decisions based on explicit, inspectable rules. Every action has a traceable, logged justification.
Compliance by design
The system's behavior is formally bounded. It meets GDPR, DORA, and SOX not because it's «configured for that» but because the architecture doesn't allow going out of bounds.
Guaranteed formal invariants
5 system invariants are verified every cycle. If any breaks, the agent stops — it doesn't act in an inconsistent state.
How it works internally
Document
PDF, Word, scanned, email
▶
input
LLM
Gemini 2.5 Pro
temp=0 · schema forzado
temp=0 · schema forzado
TYPED SENSOR
Only extracts data. Decides nothing.
▶
BeliefDelta
VERA
Cross-verification field × document
VERIFIER
0.29% hallucination. No backing → rejects.
▶
verified data
Motor BDI-HTN
Beliefs · Desires · Intentions · Tasks
DECIDES ALL
Explicit rules. Auditable. Deterministic.
▶
action
Target systems
SAP · CRM · SharePoint
Zendesk · Calendar
Zendesk · Calendar
RESULT
Full log. Every step traced.
0.29%
Hallucination rate
VERA verifies every field against the document. If it's not there, it doesn't say it.
5
Formal invariants
The system is verified every cycle. Out-of-bounds behavior: the agent stops.
100%
Traceable decisions
Every action has an explicit justification logged. Auditable by design.
0°
LLM temperature
The model operates in pure sensor mode. No creativity. No free interpretation. Only facts.
Why does this matter in regulated sectors?
Banking, insurance, healthcare, and public administration cannot use black-box AI in critical processes. Regulators require traceability, decision justification, and behavioral guarantees. An LLM-centric architecture cannot provide that by design. MIKA can — because AI never makes decisions; it only extracts verified data that a formal engine evaluates against explicit rules.
Why MIKA
AI proven in real production
No prototypes. Systems running right now with real data from real clients.
Verified precision
VERA, our extraction engine, verifies every data point against the original document before delivering it. Zero hallucinations without documentary support.
0.29% hallucination rate
Industrial speed
Massive parallel processing with Ray. Ideal for companies with large document volumes that need real-time results.
2,644 pages per minute
Integrates with what you already have
SAP, Salesforce, SharePoint, Oracle, Gmail, WhatsApp, Teams, Slack, PostgreSQL, Power Automate. We connect with your systems without migrating anything.
18+ connected systems
Production from day one
Every agent was built for a real use case, with real data, refined in production. You don't start with a prototype — you start with something that works.
Real production from day one
Multi-agent architecture
For complex use cases, we coordinate multiple agents with distinct roles that collaborate in sequence. End-to-end processing without human intervention.
64+ agents available
No AI cost
The cost of building the AI — between €200k and €400k — is already amortized. You pay for your system's development. The intelligence is included at no extra cost.
€0 additional AI cost
No setup · No code · No friction
Operational in days,
not months
We don't sell a platform your team has to learn. We connect, configure, and deliver. You start seeing results from the first week.
01
We connect to your systems
SAP, SharePoint, Gmail, Outlook, Oracle, Salesforce, WhatsApp Business, Teams, Slack, PostgreSQL, any API. No data migration, no touching your existing infrastructure.
02
Agents go live
We configure each agent for your specific use case. Your documents, your rules, your business logic. Without your team having to do anything. The first result arrives before the weekend.
First functional deliverable in days, not weeks
03
Web panel for your team
If you want to adjust rules, view metrics, review logs, or change parameters — you have a web panel ready. No code needed. No calling a technician. But if you prefer we manage it, we can do that too.
Running autonomously doesn't mean running blind — full control when you need it
The competition
- A platform your team has to learn
- Weeks of setup before seeing anything
- External consultants billing by the hour
- Projects that start in 3 months
- Separate and variable AI cost in every invoice
VS
MIKA
- We configure everything — your team just uses it
- First functional result in days
- A team that knows the system end to end
- You start the week you sign
- Fixed monthly price — AI included
See a demo with your own documents
No commitment · No prior installation · In 45 minutes you see your data processed live
Zero error tolerance environments
Autonomous agents where
making mistakes is not an option
In banking, finance, and regulated environments, an incorrect answer is not an inconvenience — it's a legal, reputational, or financial problem. Our agents are specifically designed to operate where errors have real consequences.
0.29%
hallucination rate — the lowest in the market
100%
of responses with verifiable and traceable sources
0
responses without documentary backing delivered to the user
Why they don't hallucinate
Most AI agents generate plausible responses. Ours only delivers a response when it can cite exactly where each piece of data comes from. If there's no verifiable source, it doesn't respond — and it says so.
Each statement is verified against the original document before output. Each piece of data is anchored to its exact region in the source. The system doesn't reason toward an answer — it verifies that the answer already exists in the data.
Golden rule: if it's not in the data, the agent doesn't say it. It never fills in with inferences. It never completes with probabilities.
What that means in practice
A client asks about available balance — the agent queries the source in real time and responds with the exact figure or doesn't respond.
An analyst requests the conditions of a contract — the agent cites the exact clause with page number and paragraph.
An auditor requests traceability — each agent decision has a complete log with source, timestamp, and version of the document consulted.
The system detects an inconsistency between two documents — it alerts the human instead of arbitrarily choosing one.
Sectors where we operate
Banking
Automatic analysis of loan contracts, detection of inconsistencies in client documentation, verified responses on financial products, complete traceability for compliance.
Documentary risk analysisAutomated KYCContinuous auditing
Financial & Insurance
Claims processing without interpretation errors, extraction of policy conditions with cross-verification, documentary fraud detection, automated regulatory reporting.
Claims processingPolicy analysisDocumentary fraud
Legal & Compliance
Contract review with risk clause identification, version comparison with change detection, verified precedent search, regulatory reports with full traceability.
Due diligenceContract reviewRegulatory reports
Healthcare
Extraction of clinical data from records with consistency verification, processing of medical reports without loss of critical information, document management with traceability for health audits.
Clinical recordsMedical reportsHealth auditing
Public Sector
Processing of administrative files with legal requirement verification, tender management with verified condition extraction, full traceability for transparency and inspections.
Administrative filesTendersTransparency
Infrastructure & Energy
Analysis of supply contracts with critical condition detection, processing of technical documentation with consistency verification, automatic regulatory compliance auditing.
Supply contractsTechnical documentationRegulatory compliance
Regulated environments · Banking · Insurance · Legal · Healthcare · Public Sector
Do you operate in an environment where mistakes are not an option?
We work with technical and compliance teams to define exactly which agents you need, what anonymization guarantees apply to your case, and what deployment architecture is right for your regulated environment.
The quote includes use case analysis, architecture proposal, and development estimate. No commitment.
Request a quote
For high-criticality environments
Use case analysis at no cost
Architecture proposal included
Compliance requirements assessment
Detailed development estimate
No hiring commitment
We respond in less than 24 business hours
Complete catalog
73+ agents ready to integrate
Filter by category or browse all. Each agent includes description, capabilities, and a real-use example.
Classification Agents
6 agents
LEXIS — Intelligent Document Classifier
Learns to classify your documents automatically without manual intervention. Improves with use.
- PDF, Word, scanned images, emails
- 96.8% accuracy in production
- Learns from your own documents
- Integrates with any existing system
Real example: Company with 2,211 AEAT documents — 40 different types classified automatically in production.
MOSAIC — Multi-domain Classifier
Separates and classifies documents from multiple business areas without cross-contamination between categories.
- Multiple business lines or departments
- Each domain completely isolated
- Scales without retraining
- Ideal for corporate groups
Example: Group with legal, financial and HR areas — each document goes to the correct domain without mixing or confusion.
Conversation Classifier
Automatically classifies each message, thread, or conversation by type, urgency, intent, and department.
- Urgency, intent, and sentiment detected
- Works across any channel simultaneously
- Tags and routes without human intervention
- Compatible with all your channels
Example: Call center receiving 500 daily messages — classified and routed automatically without anyone reading them first.
Query Classifier
Distinguishes between support, sales, complaints, information, and urgency across any channel in real time.
- Real-time intent detection
- Automatic prioritization by type
- Unifies classification across all channels
- Reports patterns and trends
Example: E-commerce — every incoming query prioritized automatically: urgent returns to the front, catalog questions to the bot.
Sentiment Classifier
Detects frustration, satisfaction, urgency, and abandonment intent in every customer message.
- Detection of at-risk customers
- Real-time alerts for critical cases
- Sentiment metrics by channel and period
- Notifies the responsible party when there's a risk
Example: SaaS detecting users about to cancel by the tone of their tickets — proactive intervention before they unsubscribe.
Unified Multichannel Classifier
A single brain classifying Instagram, Facebook, WhatsApp, Telegram, Slack, Teams, and email simultaneously.
- Consistent criteria across all channels
- Consolidated view of all incoming volume
- No need to configure rules separately per channel
- Unified reports from all channels
Example: Company with presence on 6 channels — a single dashboard with everything classified under the same criteria, no duplicates or noise.
Extraction Agents
7 agents
VERA — Verified Data Extractor
Extracts data from any document and verifies each result against the original before delivering it. The most accurate on the market.
- 0.29% hallucination rate
- Anchors each piece of data to its exact region in the document
- Contracts, invoices, files, forms
- Automatic verification of each extracted field
Example: Law firm processing 300 monthly contracts — VERA extracts all key clauses with evidence of where each piece of data comes from.
File Extractor
Processes complete files end-to-end, automatically identifying and extracting all relevant fields.
- Dates, amounts, names, references, statuses
- Exports to your database, ERP, or management system
- Handles files of tens or hundreds of pages
- Detects missing or incomplete documents
Example: Public administration receiving 200 daily files — processed, validated, and loaded into the system in minutes.
Invoice Extractor
Processes invoices from any supplier and format without prior templates. Exports directly to your ERP or accounting system.
- Supplier, date, amount, detail lines, IBAN
- Works with hundreds of different suppliers
- Validates against the supplier catalog
- Detects anomalies and duplicates
Example: Company with 1,500 monthly invoices from 200 suppliers — processed, validated, and loaded into SAP without human intervention.
Contract Extractor
Reads legal contracts and extracts the clauses that matter. Alerts on critical dates and risk clauses.
- Parties, dates, obligations, penalties
- Automatic renewal alerts
- Compares contracts to detect differences
- Automatic executive summary of each contract
Example: Company with 500 active contracts — automatic alert 90 days before each expiry with a summary of conditions.
Form Extractor
Digitizes and structures any form, whether PDF, scanned paper, or handwritten.
- Fields recognized without prior digital structure
- Handles handwritten and low-quality forms
- Automatically validates required fields
- Direct integration with your database
Example: Clinic receiving patient forms on paper — digitized, validated, and loaded into the clinical record in seconds.
Report Extractor
Pulls key data from PDF or Word reports and converts them into actionable metrics for your dashboards.
- Extracts tables, charts, and key data
- Consolidates data from multiple reports
- Automatically detects trends and variations
- Feeds dashboards and BI systems in real time
Example: Consulting firm receiving 50 weekly client reports — consolidated and comparable data in a single automatic dashboard.
Email with Attachments Extractor
Processes the email and all its attachments as a single structured unit. One result with all the content.
- Email body + PDF + Word + Excel + images
- Cross-references information between text and attachments
- Delivers a single structured object with everything
- Compatible with Outlook, Gmail, Exchange
Example: Agency receiving orders by email with attached documents — the agent extracts everything and opens the request in the system automatically.
Chatbot Agents
6 agents
Omnichannel Chatbot
A single agent responding on WhatsApp, Instagram, Facebook, and web simultaneously with the same consistency.
- Cross-channel conversation memory for the same customer
- Escalates to human when it detects complexity
- Tone and personality configurable per brand
- No contradictory answers across channels
Example: Online store — the customer starts on Instagram, continues on WhatsApp, and the bot remembers the entire conversation without them having to repeat anything.
Sales & Lead Generation Chatbot
Automatically converts inquiries into qualified opportunities. Collects data and schedules demos without human intervention.
- Qualifies the lead while conversing
- Collects needs and budget naturally
- Schedules meetings directly from the chat
- Feeds your CRM with every conversation
Example: SaaS B2B — the bot qualifies 200 monthly leads, schedules demos with interested prospects, and filters out those who don't fit. The sales team only talks to qualified leads.
Technical Support Chatbot
Resolves incidents before they reach the technical team, querying your knowledge base in real time.
- Step-by-step guided diagnosis
- Queries your internal knowledge base
- Opens Jira tickets when unable to resolve
- Learns from every resolution
Example: Software company — 70% of support tickets resolved automatically without the technical team's intervention.
Intelligent FAQ Chatbot
Answers frequently asked questions from your real documents. Zero hallucinations — only answers what is documented.
- Fed from your real manuals and policies
- Updates its answers when you update the documents
- Does not invent answers without documentary backing
- Metrics on what is asked most
Example: Bank that updates its policies monthly — the chatbot reflects the changes automatically without reprogramming.
File Assistant
Guides the user through any document process, answering about status, requirements, and missing documents.
- Accompanies step by step through management
- Answers about status in real time
- Reduces human team queries by 70%
- Connected to your database in real time
Example: City council — citizens check the status of their file via WhatsApp without calling or going in person.
NL-to-SQL Assistant
The user asks in natural language and gets data from their database. Zero technical knowledge required.
- Natural language questions → SQL queries
- Works on any relational database
- No need to know SQL
- Compatible with PostgreSQL, MySQL, SQL Server, Oracle
Example: Sales director asking "how much did we sell in March compared to last year?" and getting the answer in seconds without depending on the data team.
Email Agents
5 agents
Email Classifier
Automatically organizes your inbox without manual rules. Learns from your real business patterns.
- Classifies by type, urgency, and department
- Compatible with Outlook, Gmail, Exchange
- Labels, moves, and prioritizes without intervention
- Learns from your real patterns
Example: Agency with 500 daily emails — each one classified and assigned to the correct manager automatically in less than 30 seconds.
Email Data Extractor
Extracts dates, amounts, references, and names from email bodies and attachments. Exports directly to your system.
- Email body + attachments in a single step
- Exports to CRM, ERP, or database
- Handles emails with variable formats
- No extra setup per sender
Example: Importer receiving orders by email — the agent extracts quantities, references, and delivery dates and loads them into the ERP automatically.
Automatic Email Responder
Automatically replies to routine emails. Detects the type of query and generates the appropriate response.
- Uses your company knowledge to respond
- Escalates to human for complex or sensitive cases
- Maintains your company tone and style
- Log of every automatic response
Example: Service company — 60% of customer emails answered automatically outside business hours with no delay.
Email Follow-up Agent
Detects emails that require action and have not been answered. Never miss a follow-up again.
- Detects unanswered emails
- Automatic alerts and reminders
- Tracks open email threads
- Reports critical unattended emails
Example: Sales team — automatic alert when a potential client has not received a reply in more than 4 hours.
Email Routing Agent
Every email to the right department or person, automatically, with a complete audit trail.
- Analyzes content and decides who receives it
- Eliminates manual forwarding
- Configurable by rules and hierarchies
- Log of every routing decision
Example: Company with a general inbox — every email routed automatically to the correct department without anyone reading them first.
Messaging and Collaboration Agents
12 agents
Slack Monitor
Nothing important gets lost in the noise of Slack. Classifies messages and generates a daily summary for each channel.
- Monitors key channels in real time
- Alerts on keywords or critical situations
- Consolidated daily summary by channel
- Classifies by urgency and responsible
Example: Tech startup — the agent detects when someone mentions "production down" in any channel and alerts the tech team in seconds.
Slack Assistant
An intelligent assistant inside your workspace. Answers questions, searches documents, and executes tasks by command.
- Answers questions about internal documents and processes
- Searches your knowledge base from Slack
- Creates tickets, searches records by command
- Learns what is asked most
Example: Team of 50 people — the assistant answers 80% of internal questions about processes and policies without needing HR.
Automatic Reports via Slack
Your KPIs and alerts arrive on their own to the right channel. End-of-day summaries without anyone writing them.
- Automatic reports in configured channels
- Real-time alerts out of range
- Daily, weekly, or sprint summaries
- Cleanly formatted directly to the channel
Example: E-commerce — automatic report every morning in #sales with previous day's revenue, open tickets, and weekly NPS.
Slack Decision Extractor
Detects decisions and commitments made in Slack conversations. Automatically generates meeting minutes for each channel.
- Detects decisions made in threads
- Extracts implicit tasks and converts them to tickets
- Generates structured minutes of what was agreed
- Notifies the team with daily summary
Example: Product team — every design decision made in Slack is automatically documented in Confluence.
Microsoft Teams Assistant
Artificial intelligence inside your corporate Teams. Searches, responds, and executes tasks without leaving Teams.
- Searches SharePoint, OneDrive, and Confluence
- Creates tickets and tasks by command
- Compatible with Microsoft security environment
- Responds about internal documents in real time
Example: Corporation with 500 employees — the assistant answers questions about internal policies by consulting SharePoint in real time.
Microsoft Teams Monitor
Full visibility over your Teams channels. Detects conversations requiring executive attention.
- Monitors channels and chats by keywords
- Real-time alerts on critical mentions
- Activity report by team and channel
- Detects unanswered conversations
Example: Service company — automatic alert to the director when a client mentions "dissatisfied" or "cancel" in any Teams channel.
Automatic Teams Minutes
Every meeting documented automatically without anyone taking notes. Automatic transcription, summary, and distribution.
- Automatically transcribes and summarizes meetings
- Extracts decisions, tasks, and responsibilities
- Distributes minutes to the team by email or channel
- Archives in SharePoint or Confluence automatically
Example: Consulting firm — all client meetings automatically documented, with tasks assigned in Jira before the call ends.
Intelligent Onboarding via Teams
Onboard new employees guided by AI from day one. Automatic tracking of onboarding progress.
- Step-by-step guidance through the onboarding process
- Answers frequently asked questions from new employees
- Assigns tasks and tracks completion
- Notifies HR of each onboarding's progress
Example: Company with 30 annual hires — onboarding process reduced from 3 weeks to 5 days with the agent as guide.
Telegram Business Bot
Your company available on Telegram with real intelligence, directly integrated with your internal systems.
- Responds to queries and orders from Telegram
- Configurable commands for your use case
- Secure per-user authentication
- Integrated with your systems in real time
Example: Operations team — controls system status and approves alerts directly from Telegram without opening any dashboard.
Critical Alerts via Telegram
Critical alerts from any system delivered straight to Telegram. Interactive response — approve or reject directly from the message.
- Real-time notifications from any system
- Configurable by type, channel and owner
- Interactive response directly from the message
- Ideal for system monitoring and operations
Example: Server infrastructure — alerts in Telegram when any service goes down, with an acknowledgment button directly in the chat.
Telegram Group Extractor
Extract intelligence from your professional Telegram groups. Automatically captures agreements, prices and commitments from chats.
- Monitors supplier or customer groups
- Extracts agreements, prices and dates from chat
- Alerts when critical information is detected
- Daily structured summary of the group
Example: Importer with 5 supplier groups on Telegram — the agent extracts price changes and new conditions automatically.
Smart Telegram Notifications
Only interrupts you when it truly matters. Filters noise from multiple systems into a single consolidated message.
- Filters noise and only notifies what's important
- Consolidates alerts from multiple systems
- Prioritizes by urgency and your profile
- Silent outside hours except for critical exceptions
Example: CTO receiving alerts from 8 different systems — a single daily message with what truly requires their attention.
Automation Agents
5 agents
Power Automate Connector
Your AI integrated into the Microsoft flows you already use. Adds real intelligence to automations that are currently just rules.
- Connects to your existing flows without rewriting them
- Adds real intelligence to rule-based automations
- Compatible with the entire Microsoft 365 ecosystem
- No need to rewrite current automations
Example: Company with 30 Power Automate flows — the connector adds smart classification and extraction to document processing flows.
Intelligent Flow Trigger
Decides when to execute an automation based on content, not just the event. Avoids false positives in critical flows.
- Analyzes context before triggering
- Avoids false positives in critical flows
- Conditioned on multiple simultaneous factors
- Compatible with Power Automate, n8n, Zapier, Make
Example: Purchasing system — the approval flow only triggers when the amount exceeds €5,000 AND the supplier is not on the approved list.
AI Flow Processor
Inserts itself as an intelligent node inside any existing automation. Classifies, extracts or generates content mid-process.
- Intelligent node in any existing flow
- Classifies, extracts, decides or generates in the flow
- Returns structured data for the next step
- Handles errors and edge cases without breaking the flow
Example: Document intake flow — the AI node classifies the document and decides whether it goes to manual approval or is processed automatically.
Flow Orchestrator
Coordinates multiple automations as if they were one. Manages dependencies, retries and state in real time.
- Manages dependencies between different flows
- Decides execution order based on context
- Smart retries on failure
- Real-time status dashboard
Example: Company with 15 chained flows — the orchestrator ensures that if one fails, the rest wait or retry without human intervention.
Complete Document Pipeline
From raw document to structured data in the database, completely on its own. Multiple agents in chain.
- Reception → classification → extraction → verification → storage
- Zero human intervention in the standard flow
- Human oversight only for exceptions
- Full traceability of each step
Example: Tax consultancy — every document received by email processed and loaded into the system without any employee touching it.
System Integration Agents
5 agents
SharePoint Connector
Your AI working directly on your SharePoint documents. Automatically classifies, processes and organizes.
- Reads, classifies and processes documents in SharePoint
- Moves, tags and organizes based on content
- Triggers flows when it detects document types
- Compatible with Microsoft 365 and OneDrive
Example: Company with 10,000 unclassified documents in SharePoint — the agent organizes, tags and structures them in 48 hours.
ERP / CRM Connector
The AI that feeds your ERP or CRM with data extracted from documents. Creates and updates records automatically.
- Creates and updates records from documents
- Validates against existing data before writing
- Compatible with SAP, Dynamics, Salesforce, Odoo
- No custom development in the ERP
Example: Company with SAP — invoices received by email extracted and loaded into SAP automatically, without accounting team intervention.
Database Connector
Extracted data goes directly to your database, structured, clean and validated. Compatible with any engine.
- Maps extracted fields to your schema
- Validates types and constraints before inserting
- Handles duplicates and conflicts automatically
- PostgreSQL, MySQL, SQL Server, MongoDB
Example: Real estate platform — data from purchase contracts extracted and loaded into PostgreSQL without format errors or duplicates.
Document Sync Agent
Keeps your documents synchronized between different systems. Detects changes and propagates them automatically.
- Detects changes and propagates automatically
- Manages versions and edit conflicts
- SharePoint, Google Drive and proprietary systems
- Full sync log for auditing
Example: Company with documents in SharePoint and Google Drive — synced automatically, always the correct version in each system.
Industrial OCR Connector
Reads any document, even the worst scanned ones. Bulk processing at industrial speed.
- Low-quality images, skewed documents, stamps
- +2,600 pages per minute in parallel
- Scanner, mobile photo, digitized fax
- 98.5% accuracy on handwritten text
Example: Historical archive with 50,000 low-quality scanned documents — digitized and searchable in 3 days.
Monitoring and Reporting Agents
4 agents
Automated Reporting Agent
Reports generated automatically, in the format you need, without anyone writing them. Word, PDF or email.
- Consolidates data from multiple sources
- Generates in Word, PDF or email automatically
- Schedulable by frequency or event-triggered
- Written in natural language, not just tables
Example: Finance department — monthly results report generated and sent to board members automatically on the first day of each month.
SLA Monitor
Ensures your processes meet the promised timeframes. Alerts before a deadline is missed.
- Monitors each case or request in real time
- Alerts before a deadline is missed
- Escalates when it detects breach risk
- Real-time compliance dashboard
Example: Customer service with a 24h SLA — the agent alerts 4 hours before each unanswered ticket expires.
Anomaly Detector
Finds the unusual before it becomes a problem. Learns normal behavior and detects deviations.
- Learns the normal behavior of your processes
- Detects statistical deviations in real time
- Classifies anomalies by severity and type
- Integrable with any alerting system
Example: Logistics operations — the agent detects that a supplier has 3× more delays than the previous week before it affects the supply chain.
Continuous Audit System
Your processes under intelligent surveillance 24 hours a day. Automatically detects anomalies, delays and deviations.
- Monitors workflows in real time
- Automatically detects delays and deviations
- Generates automatic reports by period
- Full traceability for external audits
Example: Regulated company with frequent audits — the system automatically generates all traceability required by the auditor in minutes.
Semantic Search Agents
3 agents
Enterprise Semantic Search
Finds what you need even if you don't know exactly how to search for it. Search by meaning, not by keyword.
- Understands synonyms, variations and context
- Works on internal documents and knowledge bases
- Results ranked by real relevance
- 69.9× faster than conventional search
Example: Law firm — searches for "contracts with a penalty clause for delay" and finds all relevant contracts even if they don't use those exact words.
PC-RAG — Partitioned Retriever
The search engine that understands your company has separate areas. Retrieves from the correct domain without mixing contexts.
- Retrieves from the correct area without mixing contexts
- Ideal for companies with independent departments
- Precise answers without noise from other areas
- 69.9× faster than conventional RAG
Example: Group with legal and financial areas — a question about contracts only searches the legal domain, without contaminating with financial documents.
Multi-hop Reasoning Search
Answers complex questions that require crossing information from multiple documents. Chain reasoning.
- Crosses information from multiple sources
- Answers questions that no single document can answer
- Cites exactly where each piece of data comes from
- Ideal for analysis and due diligence
Example: M&A — the agent answers "which contracts have clauses that activate in the event of a change of control?" crossing 200 documents in seconds.
Optimization Agents
12 agents
Spark Optimizer
Analyze Spark Code
Inspects notebooks and repos to detect performance antipatterns and unnecessary complexity.
- Detects costly chained transformations
- Flags misplaced actions and cache usage
- Prioritizes fixes by expected impact
- Delivers an actionable engineering checklist
Example: Data team cuts technical debt in critical pipelines without rewriting the full stack.
Analyze Spark Job
Evaluates running Spark jobs to identify slow stages and operational bottlenecks.
- Breaks down timing by stage and task
- Detects skew and memory spills
- Compares jobs across historical runs
- Integrates with your current observability stack
Example: Nightly pipeline duration drops after identifying two imbalanced stages.
Optimize Spark Config
Suggests Spark configuration tuning to improve stability, cost, and runtime.
- Tunes partitions and parallelism
- Recommends memory and shuffle settings
- Validates impact before rollout
- Builds presets by workload profile
Example: Recurring ETL workload lowers compute spend with targeted memory and partition tuning.
Detect Spark Skew
Finds data skew in joins and aggregations to prevent stragglers and timeout failures.
- Automatically identifies hot keys
- Suggests salting and repartition strategies
- Isolates highest-variance stages
- Triggers early production alerts
Example: Billing workload removes stragglers and stabilizes processing windows.
SQL Optimizer
Analyze SQL Query
Analyzes SQL queries to find expensive filters, joins, and execution patterns.
- Detects avoidable full-table scans
- Flags risky join cardinalities
- Proposes equivalent rewrites
- Ranks quick wins by impact
Example: Analytics report runtime drops after simplifying expensive joins and filters.
Analyze SQL Plan
Interprets execution plans and translates costly nodes into concrete optimization actions.
- Compares current vs recommended plan
- Explains operator-level costs
- Detects regressions across versions
- Supports major SQL engines
Example: BI team catches a post-upgrade regression before it reaches production.
Optimize SQL Indexes
Recommends indexing strategy from real usage patterns while avoiding over-indexing.
- Suggests indexes by query shape
- Detects redundant indexes
- Evaluates write-side impact
- Delivers phased rollout plan
Example: Transactional system improves latency without hurting bulk insert throughput.
Tune SQL Workload
Optimizes mixed OLTP and analytics workloads by balancing priority and resource usage.
- Segments queries by criticality
- Balances throughput and latency
- Reduces peak-hour pressure
- Proposes smart maintenance windows
Example: Core database keeps SLA at peak load without overprovisioning infrastructure.
Log Analyzer
Analyze Log Patterns
Groups and summarizes log patterns to speed up technical diagnosis in distributed systems.
- Clusters recurring error signatures
- Detects suspicious event sequences
- Summarizes by service and environment
- Cuts incident-response noise
Example: SRE team identifies a recurring fault pattern in minutes instead of hours.
Detect Log Anomalies
Detects anomalies in log volume, frequency, and error type to anticipate critical incidents.
- Builds dynamic service baselines
- Alerts on unusual deviations
- Correlates with deployment windows
- Prioritizes by operational impact
Example: Payments platform avoids major outage by catching error drift early.
Correlate Service Logs
Connects events across microservices to reconstruct end-to-end failure chains.
- Automatic cross-service traceability
- Links logs by request and session
- Isolates true incident origin
- Builds a shareable technical timeline
Example: Distributed stack reduces MTTR by pinpointing the root service in minutes.
Root Cause From Logs
Generates root-cause hypotheses with traceable evidence from correlated events and logs.
- Ranks likely root causes
- Provides timestamp-linked evidence
- Suggests immediate mitigations
- Outputs postmortem-ready report
Example: Critical incident is mitigated faster with an evidence-backed root-cause hypothesis.
New optimization chart
Real impact of the new optimizer agent block
This block focuses on data-performance and observability outcomes: lower latency, lower cost, and higher operational stability.
Unoptimized5 stages · 9.4 GB
87%less shuffle
SparkOptimizer4 stages · 1.2 GB
Spark SQL
Query the optimizer will execute and improve
SELECT c.region, SUM(o.amount) AS total FROM orders o JOIN customers c ON o.customer_id = c.id WHERE o.status = 'COMPLETE' GROUP BY c.region ORDER BY total DESC
SPARK OPTIMIZER
VS
AFTER
SparkOptimizer
4 stages · 1.2 GB
87%less shuffle9.4 -> 1.2 GB
4.4xfaster18.4 -> 4.2s
-1stage5 -> 4
31%less tasks632 -> 433
0python UDFs3 -> 0
SPARK OPTIMIZER
Analyze Spark Code
POST /api/v1/agents/analyze-spark-code
25 rules R001-R025 on Spark source code. Instant regex <1ms, no LLM. Detects collect(), UDFs, unnecessary shuffles, orderBy, crossJoin.
sync<1msScala·Python
Analyze Spark Job
POST /api/v1/agents/analyze-spark-job
Runtime metrics from Spark REST API. 8 rules R101-R108: GC overhead, skew, excessive shuffle, spill to disk, CPU utilization.
syncruntimeR101-R108
Optimize Spark Config
POST /api/v1/agents/optimize-spark-config
Continuous directory monitoring. Detects changes in .scala and .py, auto-analyzes and alerts on critical findings.
daemonwatchauto
Detect Spark Skew
POST /api/v1/agents/detect-spark-skew
Step 1 findings → Gemini SSE. Generates detailed explanation of each anti-pattern and the optimization plan with savings estimation.
SSE streamGeminimarkdown
SQL OPTIMIZER
Analyze SQL Query
POST /api/v1/agents/analyze-sql-query
30 rules S001-S030 + 25 engine-specific. Auto-detects Snowflake, PostgreSQL, BigQuery, MySQL, Redshift by keywords.
sync<1ms5 engines
Analyze SQL Plan
POST /api/v1/agents/analyze-sql-plan
Upload .sql or .txt. Auto-detection of engine (WAREHOUSE→Snowflake, RETURNING→PostgreSQL, UNNEST→BigQuery).
syncmultipartauto-detect
Optimize SQL Indexes
POST /api/v1/agents/optimize-sql-indexes
SQL scripts directory monitoring. Detects changes, analyzes and blocks CI/CD if it finds costly anti-patterns.
daemonwatchpre-commit
Tune SQL Workload
POST /api/v1/agents/tune-sql-workload
SQL findings → Gemini SSE. Generates engine-specific rewrite with estimation of saved credits/cost.
SSE streamGeminiengine-aware
LOG ANALYZER
Analyze Log Patterns
POST /api/v1/agents/analyze-log-patterns
20 static rules L001-L020. Detects OOM, deadlocks, timeouts, segfaults, auth failures. Auto-detected format: JSON, log4j, syslog, Apache, Python.
sync<5ms6 formats
Detect Log Anomalies
POST /api/v1/agents/detect-log-anomalies
5 temporal rules T001-T005: spikes, trending, gaps, bursts, periodic patterns. Identifies systemic causes in time series.
temporalT001-T005time series
Correlate Service Logs
POST /api/v1/agents/correlate-service-logs
Real-time monitoring of log files. Analyzes new lines on the fly and immediately alerts on OOM, deadlocks and anomalies.
daemonrealtimealerts
Root Cause From Logs
POST /api/v1/agents/root-cause-from-logs
LogAnalyzer findings → Gemini SSE. Generates executive report with root cause, impact and remediation plan by role (Dev/Ops/DBA).
SSE streamGeminiroles
Custom development
Did you not find
what you need?
Building agents over time gave us something even more valuable than the agents themselves: a reusable component base that accelerates any new development.
A new classifier is not built from scratch — LEXIS is combined with your business logic. A WhatsApp agent for your specific industry takes the existing chatbot core and adapts it. A pipeline for your specific use case assembles pieces that are already proven in production.
What would take another company 6 months takes us weeks. Not because we do it fast and poorly — but because 70% is already done.
How it works when it's not in the catalog
You describe the problem
Not the agent you think you need — the problem you want to solve. We choose the architecture.
We analyze which components to reuse
From the 57 existing agents and their internal components, we identify what percentage of development is already done.
We build only what's missing
The new agent reuses existing extractors, classifiers, connectors, and verifiers. Only the specific logic for your use case is developed.
First functional deliverable in weeks
Not months of project work. Something running in your system, with your data, that you can evaluate before committing to full development.
There has been no use case we couldn't solve by reusing what we already have. If it involves documents, data, communication, or processes — we already have the foundation.
Interactive demo — 64 agents
Try any agent
in seconds
Select an agent from the panel, see how it processes real data from your industry, and what it delivers as output.
Select an agent
Choose any of the 64 agents in the left panel to see a live demo with real data
Real-time simulation
Automatic processing queue
See how MIKA receives emails, files, and documents, classifies them, extracts data, and executes actions, all without human intervention.
0
Documents received
0
Processed successfully
0
Currently processing
—
Success rate
—
Average time
Scheduled tasks
Received0
Classifying0
Extracting0
Completed0
Activity log
Available RPA workflows
End-to-end processes that combine multiple agents. Each workflow connects data input, classification, extraction, validation, and action in target systems.
Full documentation
User manual
Complete guide for each agent: what it does, how it works, how to configure it, and real usage examples.
61+
documented agents
10
agent families
123+
real examples
Select an agent
Choose any agent from the left panel to view its complete documentation
Real-time data
Operational Dashboard MIKA
All your documents, agents, and automation flows visible in one place — updated in real time and integrated with Power BI.
LIVE
FAC-2025-08821.pdf → SAP ERP ✓ contrato_renovacion_v3.pdf → SharePoint ✓ albaran_0312.jpg → Manual review FAC-2025-08822.pdf → SAP ERP ✓ notificacion_AEAT_IVA.pdf → Case created ✓ informe_Q4_2024.pdf → Power BI ✓ reclamacion_urgente.eml → Zendesk #TK-4821 ✓ FAC-2025-08821.pdf → SAP ERP ✓ contrato_renovacion_v3.pdf → SharePoint ✓ albaran_0312.jpg → Manual review FAC-2025-08822.pdf → SAP ERP ✓ notificacion_AEAT_IVA.pdf → Case created ✓ informe_Q4_2024.pdf → Power BI ✓ reclamacion_urgente.eml → Zendesk #TK-4821 ✓
agente-db-powerbi
Extraction · Calculation · Rendering
Waiting for RPA data…
Connected sources
SAP Business One
sap://erp.empresa.local:8080
ON
Salesforce CRM
api.salesforce.com/v58.0
ON
Zendesk Support
empresa.zendesk.com/api/v2
ON
MongoDB Atlas
cluster0.mika.mongodb.net
ON
Redis Cache
192.168.1.33:6379
ON
Query running
-- Waiting for data
-- Start the RPA simulation
-- Start the RPA simulation
— ms
Processing pipeline
1
CONNECT
Connecting sources…
2
QUERY
Running SQL queries…
3
EXTRACT
Extracting dataset…
4
TRANSFORM
Applying DAX calculations…
5
CACHE
Saving to Redis…
6
RENDER
Updating visualizations…
Agent metrics
Executed cycles
0
Processed rows
0
Average cycle time
—ms
Cache hit rate
—%
Last query
—
Agent log
[init] agente-db-powerbi v2.1 loaded
[init] Connecting to 5 data sources…
[ok] SAP, CRM, Zendesk, MongoDB, Redis → OK
[wait] Waiting for RPA pipeline events
Processed documents
2.122
↑ +2,122 this session
Success rate
96.9%
✓ Above the 95% target
Average time
2.1s
✓ Within the 5s SLA
In progress now
8
8 in active queue
Documents by type
Processed in the current session
⊞
Volume over time
Completed documents — last 30 events
⤢
Distribution by type
% of total processed
VERA accuracy
Success rate vs 95% target
OK vs Manual review
By document type
Processing time
Seconds by type — bubble size = volume
Recent activity
Latest documents processed by agente-db-powerbi
| Document | Type | Agent | Time | Status | Destination |
|---|
How much is it worth not paying for AI?
Tell us what system you want to build. We tell you which agents belong in it, which contracts we would read, which alerts we would generate — and how much only the development costs.
Free demo
We show you the agents working with data from your industry
Custom proposal
We tell you exactly which agents you need and what development costs
First deliverable in 30 days
Not months of project work — something running in your system in one month