We embed within engineering teams, build working AI systems, and leave teams capable of running them independently.
We embed within client teams, diagnose where AI creates genuine operational leverage, and build working systems. Every engagement ends with a working system and a team capable of running it independently.
I work inside your codebase, your processes, and your delivery cadence. I diagnose where AI creates genuine operational leverage, build working systems, and leave your team capable of running them without me.
Start an EngagementYou own the engagement and the commercial terms. I embed, build, and ship. White-label or co-branded depending on what the engagement requires.
Partner With UsMost AI engagements fail not because the technology doesn't work, but because the people implementing it don't understand economic incentives, organisational behaviour, or how technology actually gets adopted at scale versus how it gets hyped. A productivity gain that looks good in a demo but doesn't survive contact with how a business actually operates is not a gain. This context shapes every engagement I take.
I have shipped SDKs across 15+ languages, architected solutions across enterprise accounts in logistics, fintech, and healthcare, and built live products across HRMS, payroll, school ERP, drone firmware, and precision agriculture — simultaneously, not sequentially. I have operated across AWS, Azure, serverless, cloud-native, and bare metal. React, Python, Ruby, Go, Rust, Java — I meet clients wherever their stack is.
Underneath all of it is deep foundational knowledge of operating systems, networks, and protocols — not as a user of abstractions but as an engineer who has implemented IPSec, PKI, SAML, HTTP proxy internals, SSL termination, and real-time pub/sub infrastructure at production scale. AI tooling — agentic workflows, RAG pipelines, multi-model orchestration across cloud and local models — is embedded into how I operate across my own ventures simultaneously.
Define the problem, the integration points, and the success criteria. No open-ended retainers.
Inside your team, codebase, and delivery cadence. We work the way your engineering team works.
Your team runs the system independently when we leave. That is the definition of success.
Deployed an agentic document processing pipeline reducing manual classification time by 70%.
Built computer vision quality inspection for a precision manufacturing line, catching defect classes previously requiring manual inspection.
Shipped edge AI diagnostics into connected hardware enabling predictive failure detection before warranty claims.
Built real-time load forecasting reducing route inefficiency across a regional distribution network.
Integrated drone telemetry with field sensor data into an operations platform giving agronomists actionable per-plot decisions.
Embedded agentic workflow automation into an existing product team, shipping AI-native features within their existing delivery cadence.