Technology Partners

We build on the most capable foundation models and AI platforms available. Whether you need GPT-4, Claude, or open-source models via Hugging Face, we select and integrate the right provider for your use case — balancing accuracy, latency, cost, and data residency requirements.

OpenAI

Anthropic

Google Gemini

Meta Llama

Mistral AI

Cohere

Hugging Face

Replicate

Modern AI applications require sophisticated orchestration — RAG pipelines, agent workflows, tool calling, and multi-step reasoning chains. We use battle-tested frameworks to build reliable, maintainable AI systems that go far beyond simple API wrappers.

Production AI systems need continuous monitoring, evaluation, and governance. We instrument every LLM call with tracing and observability, run automated eval pipelines to catch regressions, and provide the dashboards and alerts that keep your AI reliable and cost-effective.

RAG-powered applications depend on fast, accurate retrieval from large knowledge bases. We deploy and manage vector databases that store embeddings at scale, enabling semantic search, document retrieval, and knowledge-grounded AI responses with sub-second latency.

Enterprise AI workloads demand secure, scalable, and compliant infrastructure. We deploy across all major cloud providers — with data residency controls for EU and US — and use edge computing for latency-sensitive applications. Your data stays where it needs to be.

AI systems are only as good as their data pipelines. We build automated data workflows that extract, transform, and load data from your existing systems — keeping your AI models fed with fresh, clean, well-structured data without manual intervention.

Beyond vector search, production AI applications need reliable transactional storage and high-speed caching. We use PostgreSQL for structured data and Redis for session state, caching, and real-time feature serving — proven technologies that enterprise teams already trust.

AI-driven lead scoring and pipeline intelligence only work when they surface inside the tools your sales team already uses. We integrate natively with major CRM platforms so scores, predictions, and next-best-actions appear where reps work — no new tools to learn.

We don’t just build AI systems — we make them observable. Full-stack monitoring from infrastructure metrics to LLM trace analysis, with dashboards, alerts, and SLOs that keep your team informed and your SLAs intact.

AI features ship through the same pipelines as the rest of your software. We containerize models, automate deployments, manage infrastructure as code, and integrate eval gates into your CI/CD pipeline — so every release is tested before it reaches production.

Enterprise AI deployments require robust access control, secrets management, and compliance infrastructure. We integrate with your existing identity provider and ensure all credentials, API keys, and sensitive configuration are managed securely.

AI agents and chatbots need to meet your users where they work. We deploy across web, mobile, and enterprise collaboration platforms — with webhook-based integrations that connect your AI systems to the rest of your tech stack.

Our engineering team works primarily in Python for ML/AI workloads and TypeScript for web applications and API services. This dual-language approach gives us the best of both ecosystems — Python’s unmatched AI/ML libraries and TypeScript’s type safety for production services.