You already have good engineers. What you need is someone who has gone deeper on one specific problem — and can save you months of trial and error. We advise on Generative AI, IoT & embedded, and AWS at a level that satisfies both the boardroom and the whiteboard.
Specific, high-stakes questions where depth pays for itself
An independent read on your system before you commit. We pressure-test the design for scale, cost, resilience and security — and tell you plainly what we would change and why.
Your cloud bill has crept up and no one is quite sure why. We find where the money goes and give you a prioritized, quantified plan. On one workload we cut the bill by 60%.
Everyone wants an AI roadmap; few are grounded in engineering reality. We help you pick where GenAI actually pays off, which models and patterns fit, and how to take it to production safely.
Firmware, protocol and edge decisions are expensive to get wrong. We bring real ESP32/ARM, assembly and Modbus experience to validate your approach before you build.
We look at your failure modes, data handling and compliance posture — the way the outage post-mortems on our blog were written, but before the outage happens to you.
Bring us in for a sprint, a design phase, or a standing retainer. Your team keeps ownership; we add the missing depth exactly when it is needed.
Low-commitment to start, scaled to the problem
A focused conversation to understand the problem and whether we are genuinely the right experts for it. If we are not, we will say so.
A fixed-scope audit or review, hourly consulting, or a short design collaboration — whatever fits. Clear deliverables, senior people only.
Many clients keep us on a light retainer as the expert on call for their AI, cloud or embedded decisions as they evolve.
Don't take our word for it — read the actual engineering
The fastest way to judge a consultant is to read how they reason. These are unedited deep dives from real work.
The full journey from a working prompt to a hardened enterprise system — architecture, RAG, security, performance, observability.
The analysis, the architecture changes and the numbers behind a major cost reduction.
A thorough treatment of a core industrial protocol — the kind of depth we bring to embedded reviews.
A forensic analysis of the us-east-1 outage and what it teaches about designing for failure.
Vector search at scale — how we think about the storage layer behind serious RAG systems.
Using LLM code generation responsibly inside a real engineering lifecycle.
Book a consultation and get senior, founder-led expertise on exactly the question that matters.