Systems built around you.
Your definitions, your workflows, your integrations, your agents — built with AI leverage on the platform base, never from scratch. Custom, fast, efficient: what used to take a systems integrator a year takes a phase.
What we build
AI agents & workflows
Turn repetitive, knowledge-intensive work into intelligent systems that run themselves.
- Research and analysis agents
- Customer support automation
- Sales and revenue workflows
- Finance and operations automation
- Internal knowledge agents
- Multi-step AI workflows
AI-powered products
Build new products and experiences around AI — from prototype to production.
- AI copilots
- Intelligent search
- Recommendation systems
- Conversational interfaces
- AI-native applications
- Custom LLM applications
Enterprise AI transformation
Reimagine entire business functions around AI. We work with your teams to identify the highest-value opportunities, redesign workflows, build the technology, and drive adoption.
- Sales
- Marketing
- Customer experience
- Operations
- Finance
- Product
- Engineering
Whatever we build, it lands on the rack
Agents, products and transformation programmes all throw off the same kinds of artefacts — and they go onto the platform rather than beside it. Identity, permissions, hierarchy, the metric layer and audit already exist, so nothing gets rebuilt and nothing rots in a folder after we leave.
All of it on the base, none of it from scratch. That is the difference between a custom system and a custom project.
Your definitions
Each metric with one formula, agreed with its owners and enforced in code.
Your integrations
Pipes built against your actual schemas — core systems, ERP, CRM, HRMS, the spreadsheets too.
Your dashboards
Summaries, scorecards and drill-downs shaped to your hierarchy and your review cadence.
Your workflows and apps
Ticketing, worklogs, OKRs, hiring flows — the internal tools your teams live in, rebuilt where they leak time.
Your AI agents
Plain-language answers computed from governed definitions, with defined use cases and guardrails.
Your planning models
Business model, P&L, cashflows, projections and scenarios on the same layer as the actuals.
A year becomes a phase
The old systems-integration timeline wasn't slow because people were lazy. It was slow because every project started at zero and every line was written by hand. Neither is true any more.
The platform head-start
Identity, hierarchy, the metric layer, dashboards, connectors — the T supplies the skeleton, so custom work starts at eighty per cent, not zero.
AI writes the delta
Most of the remaining code is AI-built. That is the cost collapse that makes bespoke systems viable at mid-market prices — the reason this is possible now and wasn't three years ago.
Reviewed, not vibed
Every line is read by the engineer who will answer for it, and tested against your data before it goes near a review. Speed comes from the head-start, not from skipping the check.
Tokens, passed through at cost
You pay for what the machine actually uses — no markup, no seats, a token budget per phase so the spend stays predictable. We make money when the phase lands, not when the meter spins.
Built on the platform, never beside it — so every build compounds instead of rotting alone. AI-assisted from-scratch builds are just a dev shop with better tools.
See a phase, scoped
Bring one metric your teams disagree on, or one tool that leaks time — we'll show you what a 90-day phase against it looks like.