Every technique we recommend to a client, we have first run at our own expense — multi-model workflows, agent harnesses, retrieval systems, provider failover. These are the products that came out of it. They are live, they take real payments, and you can go and use them today.
From napkin sketch to investor-ready, in a weekend. A rapid prototyping platform that takes a founder's raw concept through to presentation-ready material — built on a multi-provider AI backend with automatic failover across eight-plus LLM providers, so a single vendor outage never stops a run.
An AI coach that lives in Telegram — no app to download, no dashboard to manage. It remembers your goals and history across conversations, reaches out first with daily nudges and weekly reviews, and reads the photos you send: meals, workout screenshots, gym equipment. Starting with fitness, extending to sleep, nutrition, and skill-building. Pay-as-you-go at a fraction of the cost of a human trainer.
Pay-as-you-go SaaS that turns a resume and job description into a truthful, ready-to-submit application package — tailored resume, voice-matched cover letter, interview prep, and ATS scan — via a multi-model LLM workflow with a devil's-advocate challenge step. Every run ends with a verdict, and you only pay on a proceed.
Assemble a council of frontier AI models — US closed-source labs (Claude, GPT, Gemini) alongside the Chinese open-source frontier (Kimi, GLM, DeepSeek, Qwen) — and assign each a role: Chair, Skeptic, Senior Expert, Devil's Advocate, Synthesizer. The models deliberate in parallel without cross-talk, then return one synthesized verdict that preserves disagreement rather than smoothing it away. Pay-as-you-go, no subscription.
A marketplace connecting Victorian farmers with B2B buyers and food rescue organisations, turning surplus produce into impact. Farmers snap a photo and set a price; AI handles the listing, dispatch, and payment — so nothing goes to waste. Farmers pay zero fees while buyers are charged a 10% commission.
The work we do for clients is the regulated-sector version of this: AI assurance and governance, production AI that survives contact with real operations, and modernisation of systems built long before any of it existed.