AI that does
the expert work.
We build production AI that automates work that used to need a scarce expert — diagnosing incidents, building apps from plain English, answering your ERP. Eval-tested, self-hosted, and yours to own.
- TAFI 279/279 evalplain English a working app
- Orions ≤ 240s · read-onlyan incident a cited root cause
- VistaGPT 95.3 / 100plain English validated T-SQL
- Voice AI 24/7 · £25K/yr saveda missed call a booked job
Most enterprise AI
never ships.
You ran the POC. The demo convinced everyone. Then it hit the real pipeline, your data, your edge cases, your compliance team. Three months later the agent still fails 15% of evals and no one will sign off.
The problem was never the model. It's that the system was never built for production: no eval harness, no regression gate, no monitoring, no graceful fallback. A notebook and a prayer.
We build it right the first time, with the architecture that makes it testable, deployable and maintainable.
Six systems.
One engineering standard.
Every system ships with an eval harness, a CI regression gate and full observability, from day one.
Exhibits. Real systems,
real metrics, real clients.
Three in production, each past a complete eval harness before sign-off, plus one in active development, shown without a score. Nothing here is a demo.
Plain English → a complete, registered TechAppForce application. 96 live API calls per build, in exact dependency order, no manual intervention.
Incident report → evidence-backed RCA published to Azure DevOps. Zero analyst time. Strictly read-only, enforced at the framework level, not by policy.
Plain English → validated T-SQL against Viewpoint Vista ERP. 74.5% → 20.5% hallucination reduction. Power BI generation: 12 hours → 5 minutes.
A passive intelligence layer that reads the organisation and surfaces decisions, blockers and flight risks. In active development for our first enterprise client.
Where automations
actually pay off.
Ten production automations, grouped by the part of the business they run. Each is a documented build, deployed in days, not a demo. Pick the closest fit and read exactly how it works.
Don't read about it.
Let an agent call you.
The same Vapi-orchestrated voice AI that recovered a £25K/yr receptionist for A&A. Pick a scenario, enter your number, and hear it handle a real call, live.
See the voice build →Diagnose first. Build
second. Ship with proof.
Two engagement models. Both include full ownership, eval testing and production deployment.
Engineering Program
Custom architecture, full engineering practice.
- Full discovery, architecture & requirements phase
- Multi-agent system or agentic pipeline, built from scratch
- Complete eval harness, must pass before production
- CI regression gate against future quality drift
- Full observability from day one (LiteLLM + Langfuse)
- Documentation and 30-day support at handoff
Agentix Rapid
One scoped automation, live in days.
- Scope call to define the automation boundary
- Single-focus automation built in 2–5 days
- QA and production deployment included
- Self-hosted, your infrastructure, your data
- 100% ownership on delivery
Explore by angle: all six solutions · five industries · about the practice
Eight things that
are never optional.
These apply to every system, in every engagement. They are the line between a POC and production software.
All external I/O routes through a typed MCP gateway. Agents never call live systems directly.
TAFI: 11 MCP tools · Orions: read-only gateway
No eval, no sign-off. Full stop. Every system carries a scored harness before it ships.
TAFI QA 100 · VistaGPT 95.3 · Orions 7 golden fixtures
A merge is blocked the moment precision drops. No silent regression ever reaches production.
Orions: CI blocks on precision drop >5pp or ECE >0.15
Deterministic grounding runs before the LLM reasons. Structural enforcement, not prompt-craft.
VistaGPT: 6 parallel ChromaDB stages + reconcile
Every agentic system has explicit confirmation points. Bypass is opt-in, never the default.
TAFI: 3 named gates · CompMate: Observer→Partner ladder
Traces, per-stage latency and cost-per-query, instrumented from day one, not day ninety.
LiteLLM + Langfuse on every system
Multi-provider routing in one layer. Instant failover, no per-service configuration.
VistaGPT: 8 services unified · Claude primary, GPT fallback
New versions run in shadow mode beside v1. Compare on real traffic before cutover.
Orions v2: DIAGNOSIS_V2 flag · GET /eval/shadow-report
Production systems running
for leading organisations.
5 construction firms in production on VistaGPT. 3 enterprise systems behind full CI gates. Every layer self-hosted, clients own it all.
An 8-person engineering practice, not an agency. Sagar Maheta is lead architect across all five systems. Meet the practice →
Production-grade,
open-source, yours.
You own every layer. No vendor lock-in. Self-hosted option on every engagement.
There's a number
hiding in your ops.
For established operations, our fixed-fee Process Audit maps every manual handoff, puts a defensible cost on the waste, and installs the agents that remove it. Check if you qualify, it takes one tap.
How the audit works →Ready to build something
that actually ships?
Tell us what you're trying to automate. We'll tell you how we'd build it, what it would take, and show you the eval score it would have to pass.