We treat AI as an untrusted advisor: it proposes, your domain logic disposes. Every model call goes through one gateway that owns timeouts, cost ceilings, and usage tracking.
In practice that means OCR pipelines that cut manual entry by ~80%, RAG assistants grounded in your data, and automation agents that handle multi-step workflows, always with a human in the loop where accountability matters.
What we deliver
LLM integration (OpenAI, Groq, self-hosted)
OCR & document intelligence
RAG-powered assistants & search
Automation agents & intelligent routing
Our approach
01
Single model gateway: timeouts, retries, token ceilings, cost kill-switch, providers swappable.
02
Human-in-the-loop by default: low-confidence outputs surfaced for review, never auto-committed.
03
Self-hosted first for sensitive data: Ollama, llama.cpp, LM Studio behind the same gateway.
04
RAG grounded in your schema: chunking, embedding, retrieval tuned per domain, not generic.
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