Diagnostic
We choose the workflow, define what success looks like in numbers, map the system's path to your data, and write the evaluation plan — before any code ships.
We build AI, and keep it running.
Most AI projects stall right after the demo. We take over from there — build it properly on your own systems, and stay on to run it.
Start a conversation ↗89%of enterprise agent pilots never reach production.Deloitte Tech Trends, 2026
Case study
Proof, not projections.
TRANSRAILEngineering & EPC
The constraint wasn't will. It was throughput.
Workforce enablement, workflow redesign, and agentic readiness — one operational intelligence layer under 64 countries of local execution.
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CONFIDENTIALInsurance & Brokerage
Faster approvals, without cutting corners on compliance.
Submission data analysis, qualification, and multi-step approval, redesigned for a high-volume brokerage — audit trail intact, security posture untouched.
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RED CORE FMFacilities Management
Compliance scheduling that doesn't depend on one person remembering.
Automated PPM, PAT testing, and legionella scheduling, AI-assisted maintenance triage, and structured outreach for a London commercial FM business.
Read more ↗It’s rarely the model.
Most AI projects don’t die because the technology doesn’t work. They die because nobody agreed what “working” meant, the system never got real access to the data it needed, or nobody kept watching once it shipped. Those are scoping and ownership problems — and they’re exactly what a proper diagnostic exists to catch before a single line of code gets written.
How the work runs.
Sprint
One workflow, built on your own infrastructure, running in production — with telemetry and a named owner inside your business. You keep the code and the weights.
AgentOS
The layer that keeps it alive: orchestration, governance, observability, evaluation, and model routing across Claude, GPT, Llama, Mistral, Qwen and DeepSeek.
The state of enterprise AI
89%
of enterprise agent pilots never reach production.
Deloitte Tech Trends, 202631%
of enterprises run at least one agent in production today.
S&P Global / McKinsey47%
in banking and insurance — the sector leading production deployment.
S&P Global / McKinsey5.1 months
median time-to-value for the pilots that do reach production.
BCG / Forrester, 2026Figures drawn from secondary coverage of Deloitte, S&P Global/McKinsey and BCG research, as of August 2026 — ask us for primary sources.
Three ways to get there.
OutcomeIn-houseLarge consultancyAventeqAI
TimelineCompetes with your existing roadmap6–18 months8–12 weeks, one workflow
InfrastructureDepends on internal capacityOften moves you onto their platformBuilt and run on your own systems
After launchNo dedicated evaluation layerHands off after deliveryAgentOS stays on to run it
What you get.
Workflow diagnostic
Pick the process, define success in numbers, and write the evaluation plan before anything gets built.
Data access mapping
Find out exactly what the system needs to reach — and what it can't — before it becomes a production surprise.
Production sprint
One workflow, built and shipped on your own infrastructure, with a named owner inside your business.
Model routing
Route across Claude, GPT, Llama, Mistral, Qwen and DeepSeek — never locked to a single provider.
Evaluation & observability
Know when it's working and when it's drifting, with telemetry built in from day one.
Ongoing governance
AgentOS keeps orchestration, access, and audit history in place after the sprint ends.
From our research.
Read the research ↗01
Design for a world where the model changes.
A production AI system should survive a provider outage, a policy change, or a better model — without forcing the workflow to be rebuilt.
03The distance from AI pilot to production is made of controls.
What actually separates a demo from a system your business can depend on.
04When AI starts acting, governance becomes part of the product.
Once an agent can take action, oversight isn't optional — it's a feature.
Let’s talk about your AI.
Tell us about the workflow, and we’ll tell you honestly what’s possible.
Start a conversation ↗