We've delivered 100+ AI projects across enterprise and growth-stage companies. We handle complexity — custom model training, full-stack Voice AI, Physical AI deployments — not just API integrations.
End-to-end voice pipeline ownership: ASR, LLM, TTS, RAG, memory — all integrated and deployed. Almost always on-premise with fine-tuned models for client-specific performance at lower cost than off-the-shelf.
Computer vision and AI systems that understand and act in physical environments. From factory floors to traffic infrastructure — we build perception systems that work at production scale.
Three ways to engage. Every engagement is staffed by engineers who train models and publish research — not just call APIs.
AI products and agents on frontier APIs — OpenAI, Anthropic Claude, Gemini — or on-prem open models like Qwen and Llama when data can't leave your infrastructure.
Where APIs fall short, we train. Classical ML, computer vision, and fine-tuned LLMs, VLMs, and embedding models for niche domains, languages, and latency budgets.
Not sure where AI pays off? We run discovery on your data and workflows, rank use cases by ROI and feasibility, and hand you a roadmap — then build it if you want us to.
Our FDEs embed directly with your team — on-site or remote, from discovery through production. You get shipped systems and transferred knowledge, not slide decks.
We're not a prompt engineering shop. We train models, design architectures, deploy on-prem, and own the outcome. Our clients come to us when the problem is genuinely hard.
Most of our clients are Fortune 500 enterprises or Series B+ startups. Engagements run from 3-week proof-of-concepts to multi-year co-development partnerships.
We work best with teams who have a real problem, not just an interest in AI.
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