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Roadmap

2 posts with the tag “Roadmap”

Bring Your Own Model: 638Labs Unopinionated Approach

Right now, in 2025, the world of AI isn’t a seamless general intelligence — it’s a loose federation of narrow, useful agents: summarizers, recommenders, translators, code fixers, search enhancers. And most of these services live behind APIs, not platforms. Especially for small and fast-moving teams, AI isn’t a monolith — it’s a patchwork of deployed endpoints.

That’s where 638Labs fits in.

What 638Labs Is

638Labs is a lightweight, developer-first infrastructure layer for deployed AI services. At its core, it offers:

  • A registry of invokable, online-only endpoints
  • A forward proxy that routes OpenAI-compatible requests securely
  • A clean separation between what you’ve deployed and how you expose it to others or your own stack

We don’t host your models. We don’t wrap your functions. We don’t enforce contracts. If it’s accessible over HTTP, we can route it.

What 638Labs Is not

We’re not a model host, fine-tuning provider, or training platform.
We don’t require you to upload files, checkpoint models, or containerize workloads.
We’re not an agent runtime like CrewAI or LangGraph — but we can route to them.

Why This Matters — Especially for Agile Teams

Teams building fast need flexibility, visibility, and control. With 638Labs:

  • You can test, trace, and switch between models quickly
  • You avoid vendor lock-in or the burden of full-stack platforms
  • You get centralized logging, routing, and basic controls without ceremony
  • You can bring your own models — OpenAI, Hugging Face, self-hosted, or anything else

You stay in control. We just forward the calls.

Use Cases

Use 638Labs when:

  • You’re prototyping new agents but don’t want to rebuild infra each time
  • You want to expose internal AI services to different clients without rewriting
  • You’re mixing commercial APIs and your own endpoints
  • You want a future path to exposing some agents publicly — without rebuilding
  • You want a stable API surface for your business or enterprise tools, while freely changing the underlying models behind the scenes
  • You want to version your AI services (dev, test, prod) and roll forward or backward as needed

Final Word

The AI world might move toward consolidation. But right now, it’s fragmented — and that’s not a bug. It’s a sign of progress, experimentation, and choice.

638Labs exists to help you route, trace, and manage that world — without getting in your way.

Bring your own model. We’ll take it from there.


638Labs is a live registry and proxy for deployed AI services.
Learn more: https://638labs.com

AI Registry - Soft versioning

Introducing Soft Versioning.

Soft Versioning for Online AI Endpoints

Most AI registries focus on models and weights. But 638Labs is built for a different world: online, deployed endpoints — models, agents, and data services that are live and callable right now.

That changes how versioning works.

Why not enforce hard versioning?

In traditional software registries or package managers, versioning is critical because you’re distributing code or binaries. But in our model, you’re pointing to a live endpoint, not downloading anything.

So instead of managing version trees or enforcing git-like histories, we keep it simple:

  • If you deploy a new version, register a new route.
    Example:
    acme/agent-v1 → original
    acme/agent-v2 → new endpoint

  • Or reuse the same route and update the metadata:

    • "version": "2.1.0"

We call this soft versioning.

This is in testing for now, will be deployed soon

Why it works

  • Keeps the registry light
  • Lets you evolve your services without breaking users
  • Encourages clear naming and route discipline
  • Avoids overengineering a version system in a space where most tools (like GitHub or your CI/CD flow) already handle source tracking

When we’ll evolve this

As we introduce public marketplaces and more collaborative agent development, we’ll expand version support — but without sacrificing the simplicity of pointing to live, callable endpoints.

Until then, soft versioning keeps things lean and developer-friendly.


638Labs is a live registry and proxy for deployed AI services.
Learn more: https://638labs.com