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.
We've grown with every wave of AI — and stayed technical throughout.
Custom model training was our default. Everything required ground-up solutions: designing architectures, collecting data, training, validating. Good foundations.
We moved with the field but stayed architectural. Our GenAI work was rarely simple RAG — we built complex multimodal pipelines where accuracy demanded it. On-prem OSS models alongside cloud APIs.
Most of our current client work is Voice AI. We build the whole system — ASR, LLM, TTS, RAG, orchestration — not just plug in APIs. We fine-tune for each client's use case to get smaller, faster, cheaper models that outperform generic large models.
We're getting increasing traction in Physical AI. Industrial anomaly detection, factory monitoring, traffic intelligence — systems that understand and act on real-world visual data. This is where our research and applied work converge.
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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