We help scale-ups design and implement AI-native engineering workflows - so one engineer does the work of five, and your team focuses on what actually moves the business. We're doing this ourselves, today.
This is already true - not in two years. The companies winning today have figured out how to use AI as a force multiplier. The gap is widening every quarter.
For investors, a 15-person engineering team without AI-native workflows is a red flag. High burn, low velocity. Burn rate is no longer a proxy for ambition.
In every tech due diligence we run, we now assess AI adoption as a direct signal of engineering maturity and competitive positioning. It matters to investors.
Most engagements start with a fixed-scope AI Readiness Audit. Almost every client converts to an ongoing engagement once they see the opportunity.
We map your current engineering workflows, identify where AI agents can have the highest impact, and flag the blockers - technical, cultural, and organisational.
We design the AI agent architecture for your specific stack and context. Which agents, which tools, which orchestration layer - and how they fit into your existing processes.
Cursor, Claude, Copilot, n8n, Supabase, LangChain - we evaluate and select the right tools for your team, then integrate them. No vendor bias, just what works.
The biggest failure mode in AI transformation is adoption. We run hands-on workshops with your engineering team - practical, not theoretical. They leave knowing how to use the tools.
We define the velocity metrics before we start and measure the improvement after. You get a clear before/after picture - useful for internal alignment and investor reporting.