Approach

Platform & MLOps Enablement

Shared services, evaluation harnesses, and tooling that help internal teams ship AI faster and safer.

Reference architecture

We design platform blueprints that align with your cloud provider, security posture, and data governance policies. Each blueprint covers retrieval, orchestration, evaluation, logging, and safety layers, plus the interfaces teams need to use them.

Core services & libraries

We implement reusable services for prompt and retrieval patterns, Bedrock/OpenAI gateways, evaluation pipelines, and structured logging. Developers access them through SDKs and templates that make the right thing the easy thing.

Integration with DevOps

Platform components plug into your CI/CD pipelines, infrastructure-as-code repos, and observability stack. We ensure AI projects inherit the same rigor as other software initiatives.

Capability transfer

We ensure internal teams can own the platform long term.

  • Playbooks explaining how and when to use each component
  • Workshops with engineering, platform, and risk teams
  • Shadowing and co-building so internal teams can evolve the platform

Need a AI platform teams actually adopt?

Let’s map your current stack, identify the highest-value shared services, and co-build the foundation together.

Plan a platform working session