ProductionAIengineering
We'reaseniorengineeringteamthatshipsAIsystemsfundedstartupscanruninproduction—voiceagents,customersupportautomation,businessrulesengines,agenticsystems.
ShippedforYC-backedhealthtech·USconsumerSaaS·Healthcarecredentialing·AIdevtools
Every engagement is anchored on work we've already shipped for funded teams. No category here is theoretical.
Voice systems built for regulated, high-stakes domains. Fallback handling, observability, and reliability from day one — not bolted on after the demo.
Autonomous resolution of customer tickets — cancellations, refunds, retention offers — measured against real conversion outcomes, not deflection theater.
For when an LLM is the wrong tool and you need deterministic, auditable logic. We build the systems regulated domains can actually defend.
AI agents with deep context about your operations. They ship features, fix bugs, and automate the work your team shouldn't be doing by hand.
We've built Loveable-style code generation systems end to end. We know what AI tooling looks like under the hood, because we've shipped it.
+ Any AI solution that your company needs
See how it played outReal clients, real production systems. The metrics and stacks are exactly what shipped — outcomes, not the pitch.
We helped build an AI call and SMS agent that handles the phones for prescription pharmacies — patient queries, prescription status, and pharmacist escalation — plus the authentication flows for the pharmacy dashboard. Core 0→1 product work, running on real call volume.
An AI agent that resolves customer queries and executes full cancellation, refund, and retention-offer workflows with no human in the loop — on Python/FastAPI services for real-time reliability, GPT-5.2 for context-aware responses, and AWS provisioned with Terraform.
A business rules engine built from scratch in Java, Quarkus, and GraalVM to replace a slow manual review process, plus the React/Next.js dashboard that surfaces rule violations per uploaded document. Native-compiled, fast, and built to be trusted with compliance decisions.
An AI coaching platform that holds an empathetic, context-aware conversation. Embedded with users — running interviews, defining the core use cases, shaping product strategy — then building it end to end, with Claude as the reasoning layer, VAPI for live voice, and prompts and behaviour tuned in Langfuse and PostHog.
A company brain that holds full context on Deeply and lives in Slack, where the whole team triggers it. It develops and ships features, reviews code, maintains the codebase, keeps internal documents current, and preserves company intelligence — turning institutional knowledge into an always-on operator.
A Lovable-style AI code-generation tool built on RooCode, FastAPI, and React — plus the auth flow, an admin analytics dashboard, and a full Stripe credit system metering LLM and compute usage.
From global enterprises to seed-stage startups — every logo here has our code running in production.
No black box. You see the work daily, own the code from day one, and walk away with a system your team can run.
We audit the current AI system or the whitespace, map the production failure modes, and define scope. You walk away owning a written technical plan — whether or not we build it.
Senior engineers embedded with your team. Daily Slack, weekly demos, code in your repo from day one. Evals and observability built in from the start, not bolted on at the end.
Production launch with monitoring, documentation, and your team trained to operate it. Most clients move into a smaller retainer for continued evolution and reliability work.
Quido is the AI engineering practice I run for technical founders. Before this, I shipped production AI for 8+ funded startups, built seller-registration infrastructure as an SDE at Amazon, and wrote a map-matching algorithm using Hidden Markov Models at Sixt R&D.
Quido itself started in 2023 as a consumer crypto investing app — we scaled it to 1,500 users and ~$20k AUM before pivoting the company to AI engineering in 2024. The fintech roots are real, and so is the lesson: shipping something people actually run is a different discipline than building a demo.
Track record
Funded startups, pre-seed through Series B/C. We work with technical founders and engineering leaders who already have an AI thesis and need senior engineering capacity to ship it.
A discovery call is a technical conversation, not a sales pitch. Bring the system that works in demo and falls over at scale — we'll tell you what we'd do about it.
