AI Platform Development
Build AI Infrastructure You Actually Own
Production-grade GenAI platforms deployed in your cloud—built on open-source, documented completely, and handed over entirely.
The Problem with AI Infrastructure Today
Most organizations face a frustrating choice when building AI capabilities: rent black-box SaaS tools that limit customization and create vendor lock-in, or spend 12-18 months assembling fragmented open-source components while your competitors ship features.
Neither path serves companies that want strategic control over their AI capabilities without diverting their entire engineering team for a year and a half.
What We Build
We design and deploy complete GenAI platform infrastructure in your cloud environment—AWS, GCP, or Azure. Every component is production-ready, fully documented, and yours to own and operate.
Container Orchestration
Kubernetes clusters (EKS, GKE, AKS) or serverless deployments configured for AI workloads, with auto-scaling, resource limits, and cost controls built in.
Infrastructure-as-Code
Complete Terraform configurations for reproducible deployments. Your ops team can spin up new environments, modify resources, and understand exactly what's running.
API Layer
FastAPI or similar frameworks providing clean interfaces for your applications. Rate limiting, authentication, and versioning included.
Vector Storage
PostgreSQL with pgvector, Pinecone, or Qdrant—selected based on your scale, latency, and portability requirements.
Model Connectivity
Abstracted interfaces to OpenAI, Anthropic, AWS Bedrock, or open-source models. Switch providers without rewriting application code.
Observability Stack
Logging, tracing, and monitoring configured from day one. Know what your AI systems are doing before users report problems.
Why Platform Architecture Matters
The difference between a demo and a production system isn't the model—it's everything around it. Platforms that work reliably at scale have:
- Clear failure boundaries. When something breaks, you know where and why.
- Graceful degradation. Timeouts and errors produce useful fallbacks, not cryptic failures.
- Operational visibility. Your team can diagnose issues without calling us.
- Cost predictability. Token usage, compute costs, and scaling behavior are understood and controlled.
We've built platforms that handle millions of requests. The infrastructure patterns are well-understood. What varies is how they're adapted to your specific requirements—your cloud policies, your compliance needs, your integration points.
Open-Source Foundation, Enterprise-Grade Execution
We build on proven open-source components: LangChain for orchestration, Kubernetes for deployment, Terraform for infrastructure, PostgreSQL for storage. Nothing proprietary. Nothing that locks you to a specific cloud or vendor.
Complete Handover
All source code in your repository, Terraform configurations for infrastructure, architecture documentation, operational runbooks, and training for your team.
Security Hardening
Enterprise-grade security practices, access controls, encryption at rest and in transit, and compliance with your organizational policies.
Performance Tuning
Optimized for production workloads with load balancing, caching strategies, and resource optimization.
Timeline
Platform builds typically complete in 8-12 weeks from discovery to production deployment.
Complex multi-region deployments or extensive legacy integration may extend this timeline. We scope precisely based on your requirements.
Weeks 1-2
Discovery and architecture design
Weeks 3-8
Infrastructure deployment and integration
Weeks 9-10
Hardening and documentation
Weeks 11-12
Training and handover
Ready to build AI infrastructure you control?
We'll map your requirements, outline an architecture, and show you what's achievable in 8-12 weeks.