Endpoint 51 engineering studio
I design and build API integrations, internal AI workflows, and backend services—with testing, observability, failure handling, and deployment included from the start.
Where I can help
The useful prototype is rarely the finished system. The remaining work is usually integration, reliability, security, evaluation, and deployment.
01 / INTEGRATE
Connect third-party services, internal systems, and inconsistent data without leaving your team with another brittle script.
02 / AUTOMATE
Use language models where they reduce real operational work, not where a conventional rule or query would be more dependable.
03 / SHIP
Strengthen a working Python service so people can depend on it and another developer can understand what happens when it fails.
A visible process
You should be able to see what is being built, why each technical decision was made, and what remains uncertain.
Define the business workflow, inspect the systems and data involved, and identify the smallest useful outcome.
Deliver in working increments with demonstrations, written decisions, and risks surfaced before they become expensive.
Deploy the system, document the operational path, and leave your team with code it can continue to own.
Evidence, not borrowed logos
The public projects and guides show the architecture, code, testing, and deployment decisions behind the finished result. They are the starting proof while Endpoint 51's client portfolio grows.
Built systems
OAuth, PostgreSQL, FastAPI, Docker, AWS, CI/CD, and async processing.
View projects →Testing approach
A complete guide to unit boundaries, HTTP mocking, authentication, and production test suites.
Read the guide →AI delivery
A practical workflow for using AI while keeping architecture, verification, and ownership visible.
Read the guide →Start with the problem
If Python, APIs, or AI are a sensible part of the solution, I’ll explain what I would investigate next. If they are not, I’ll say that too.