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Use Cases

MIKA's potential, case by case.

Here's how MIKA could intervene in the document problems of Healthcare, Insurance, Legal, Banking and Finance — using the same extraction, understanding and automation flows that already work today.

Industries with concrete examples

HealthcareInsuranceLegalBankingFinance
Industries

From a concrete document problem to a measurable result.

The following are illustrative examples of what MIKA can solve in each sector — not a client history.

These same industries, with more detail on each capability, are developed in MIKA. Explore MIKA

The problem

Clinical histories arrive handwritten and unstructured, and readmission risk or adverse effects are detected late because the information is scattered.

Documents and processes

Handwritten clinical histories, medical reports, pharmacovigilance reports

How MIKA intervenes

MIKA reads handwriting, extracts diagnoses and pseudonymizes the data automatically; then a predictive model estimates readmission risk and groups adverse-effect reports to detect patterns.

Result

Less manual transcription time, earlier risk alerts, and traceable clinical information.

Examples

Handwritten clinical historiesReadmission predictionPharmacovigilance
A pattern that repeats

The same problems, again and again, across different industries.

The sector changes, but the underlying problem repeats: information that exists, but is hard to find, structure or cross-reference in time.

Manual data entry
Handwritten documents that never get digitized
Search that depends on the exact word
Manual reconciliation between documents
Deadlines and clauses with no alert
How MIKA intervenes

Real flows with MIKA

These are the concrete mechanisms behind the cases above — what it actually looks like, step by step, when MIKA intervenes in a document process.

Extractor

Batch extraction

Capability used

Extraction with configurable templates, processed in batch.

Result for the user

The user stops entering data by hand, document by document.

Chat

Document chat (RAG)

Capability used

RAG over the documents you upload.

Result for the user

Find information without reading document by document.

NL → SQL

Chat with databases

Capability used

Natural-language-to-SQL translation over connected databases.

Result for the user

Query structured data without writing a query.

Search

Semantic search

Capability used

Search by meaning, not exact text match.

Result for the user

Find the right document without remembering the exact word.

Management

Admin panel

Capability used

Multi-tenant management with 3 roles and paginated logs.

Result for the user

Control and traceability over who uses what, without manual spreadsheets.

Possibilities

What could be built from these same capabilities.

The following are hypothetical examples — meant to show the range of businesses MIKA could apply to, not confirmed features or real client cases.

Agribusiness

Validating whether you're trading at a fair price requires cross-checking reports and contracts against market quotes.

Extraction from reports/contracts + connecting MIKA to whatever quote source the client gives it.

Retail

Comparing hundreds of catalog products every season takes time.

Multimodal extraction (text and images) over uploaded catalogs.

Industry and manufacturing

Technical manuals are hard to interpret on the floor, and preparing information for maintenance takes time.

Extraction and rewriting in plain language from manuals and technical documentation.

Advertising and marketing

Brand control over creative materials gets scattered across folders and versions.

Extraction of text, colors, logos and dates from creative assets.

Tourism

Confirming reservations and building itineraries by hand is slow and error-prone.

Extraction of reservation data and automatic structuring.

Public administration

Case files and public tenders pile up in archives, undigitized and unstructured.

Extraction and OCR (including handwriting) over administrative case files, with semantic search over the structured archive.

Human Resources

Manually entering data from CVs and employee forms into management systems takes time.

Extraction from forms and CVs, with pseudonymization of personal data.

Operations and logistics

Bills of lading, delivery notes and manifests get entered by hand into tracking systems.

Extraction of logistics documents for tracking and inventory.

Is your industry not here? Tell us about your case and we'll look at it together.

Do you recognize any of these problems in your team?

Tell us which documents and processes take up the most time, and we'll show you how MIKA intervenes in your specific case.