Production-grade AI over your own documents, on your own infrastructure.

Enterprises don’t fail at AI because the model is weak. They fail at production — turning probabilistic output into reliable, source-traceable, secure results at scale. Demos are easy; permissions, evaluation, audit logs and “never fabricate” are hard.

We build the deterministic layer enterprises need above foundation models — not a prompt wrapper.

Scope a 2-week POC I’m an SI / consultancy looking for a delivery partner →

What we deliver

Three capabilities on one stack: knowledge graph and intent routing, a template and rule engine, RAG with mandatory source citation, multilingual OCR and parsing, and local desensitisation before any AI step — so security is part of the pipeline rather than bolted on.

Intelligent document interpretation

Import → parse → understand → structured output for tenders, contracts, reports and specs.

Multi-format ingestion with OCR, auto-classification and foldering
8-dimension structured extraction into your own checklist or schema — value, unit, condition, source, confidence
Fields that aren’t in the document are marked “not specified”, never invented
One-click package export

AI knowledge management (RAG)

A private, source-cited insight repository instead of scattered reports and inboxes.

Natural-language Q&A answered with citation to document · chapter · page
Role-based permissions and tenant isolation
Immutable audit log over every query and answer

Contract & compliance review

Rule-library risk grading with every finding anchored to the clause it came from.

High / medium / low risk grading, red-line and change-diff
Seal and signature verification, negotiation-window alerts
Rules maintained in natural language by legal or finance — no code

What we commit to

These are the numbers we write into the POC and measure against — on your documents, in your environment, before any production rollout. If we miss them, you have not bought a production system and we have not earned the rollout.

≥ 90%: extraction accuracy; on key parameters and risk clauses
100%: source-traceable; every value anchored to doc · chapter · page
≥ 98%: run consistency; same input, same output — production, not gacha
6: languages; CN · EN · FR · ES · RU · PT, OCR and parsing

On-premise by default. Sensitive data never leaves your servers; local desensitisation runs before any AI step. Private and air-gapped deployments supported.

Who builds it

Jay Wang — founder, AI lead

16+ years in AI and data: Head of AI at ByBit, previously Principal Applied Science Manager at Microsoft and Director of Data Science at Kuaishou. Ph.D. in Statistics. Author of Building Recommender Systems Using LLMs (Springer, 2025) and a repeat speaker on RAG and enterprise LLM systems.

Applied-AI team

Computer vision, speech and generative video, with production pipelines shipped across crawling, transcription, translation, TTS and synthesis — plus a reference architecture for six-language, on-premise tender interpretation and contract review scoped for a listed power-industry manufacturer. (That engagement is in progress; we cite it as architecture and approach, not as a delivered reference.)

How we engage

For enterprises

A 2–4 week paid POC on one real workflow

We take one of your actual documents or workflows, run it end to end, and measure against the commitments above. Standardised scope — not open-ended custom development. Production rollout follows the POC, or it doesn’t.

Book a 30-minute discovery call

For systems integrators & consultancies

White-label AI delivery partner

You hold the framework positions, the qualifications and the client relationship. We deliver the agent / RAG / document-intelligence core underneath your name. Useful where a bid is technically weighted and the AI depth is the scored part.

Talk about a partnership

Typical starting points

A knowledge-management or market-intelligence repositoryinsight repo with cited answers — capability 02
An audit or financial data-extraction platformstructured extraction plus audit trail — capability 01
Tender and contract interpretationchecklist extraction and risk review — capabilities 01 + 03

Bring us one document you dread.

The fastest way to find out whether this works on your data is to run it on your data. Two weeks, fixed scope, measured against the numbers above.

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