Why most enterprise
GenAI never ships.
The demo works in the room, then stalls. Industry research puts GenAI pilot failure north of 80%, and the model is rarely the reason.
Industry research · 2025
80
%
+
of enterprise GenAI pilots never make it to production.
The demo works in the room. Then it stalls.
And the model is rarely the reason.
01
Built on a laptop
The pilot ran on a demo box, not your infrastructure, so it never survived real users.
02
No one could trust it
It hallucinated off-script and couldn’t explain itself, so legal and security said no.
03
Never connected to anything
It never reached your ERP, CRM, or document store, so nothing changed on the floor.
Cost of inaction
GenAI services are growing ~43% a year. The market isn’t waiting for pilots to finish.
CAGR
2020–25
Services
What we build
Systems your team uses on day one and trusts on day ninety, not prototypes you rebuild later.

LLM Apps
Custom LLM applications
Copilots, document drafting, report generation, and knowledge assistants built on your data and wired into the tools your team already uses every day.
Built on your data
Wired into tools you already use
RAG
RAG systems
Answers grounded in your manuals, SOPs, tickets, and contracts, with citations. Accurate on your domain, not confidently wrong.
Answers with citations
Grounded in your documents


Models
Foundation model integration
Model-agnostic. GPT, Claude, Gemini, Llama, or self-hosted, chosen on accuracy, cost, latency, and data residency. No lock-in.
GPT, Claude, Gemini, Llama & more
No vendor lock-in
Documents
Document & knowledge automation
Extract, classify, summarize, and route invoices, inspection reports, and compliance paperwork. Where teams with heavy document loads see payback first.
Extract, classify, summarize, route
Fastest payback for document-heavy teams


Production
POC-to-production hardening
Security review, evaluation harness, guardrails, integration, deployment, and monitoring. The engineering that turns a stalled demo into a system of record.
Security review & guardrails
Deployment & live monitoring
Architecture & Pipeline
Built for production, not the demo
A demo is one happy path. Production is every edge case, bad input, and question nobody anticipated. The difference is architecture.
Step 1
Ingest
Connect to your sources, document stores, databases, ERP, CRM, inside your environment.
Step 2
Process
Clean, chunk, and index so the model has grounded context, not the open internet.
Step 3
Model
The foundation model does language and reasoning, constrained to the context you gave it.
Step 4
Human check
For anything consequential, a person approves before action. You set the line.
Step 5
Integrate
Output flows back into the tools your team already uses, no orphan dashboard.
Step 6
Monitor
We track accuracy, drift, cost, and usage live, and alert when something moves.
Where it earns its keep.
GenAI pays back where there’s unstructured knowledge and repetitive manual judgment. The patterns we build most:

01 / 04
What we ship
SOP assistant
Inspection report drafter
Defect triage
02 / 04
What we ship

62%
deflection on tier-1 support

10×
throughput on doc workflows
03 / 04
What we ship
04 / 04
Engineering & R&D
Code assistants, spec and doc generation, search across large technical archives.
What we ship
Code copilot
Spec drafter
Technical archive search

35%
faster PR cycle time
AI Trust & Governance
Your data, your control, your audit trail.
We don’t believe in black-box AI. Our methodology shows you exactly what we’re building, how it’s grounded in your data, and where humans stay in control—before a single line of code is written.


