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Architecture and migrationBrief

How to avoid LLM vendor lock-in without limiting your product

Vendor independence does not mean avoiding every useful feature. It means isolating dependencies, measuring substitutes, and keeping model choice reversible.

By INFRO Editorial

Published

Updated

1 min read

An application escaping a single closed AI path into an open constellation of model choices

In short

Avoid LLM vendor lock-in by isolating provider contracts behind one client boundary, keeping prompts and evaluations portable, storing your own operational data, and continuously testing substitute models. Independence is the ability to switch with evidence, not the refusal to use provider features.

Identify the real lock-in layers

SDK syntax is the shallowest layer. Deeper dependencies include proprietary tool semantics, prompt tuning, safety behavior, fine-tunes, hosted retrieval, cached state, media formats, evaluation assumptions, and operational dashboards.

Inventory dependencies explicitly. A standard API helps, but it cannot make model behavior identical.

Create a narrow inference boundary

Centralize authentication, base URL, timeouts, retries, model IDs, and response normalization. Expose the capabilities the product needs rather than every provider field.

Allow a controlled escape hatch for genuinely valuable provider features. Keep it isolated and covered by a migration decision, not scattered through the codebase.

Make portability measurable

Maintain an evaluation set and run it against at least one substitute for every important workload. Record quality, schema reliability, latency, and cost. A fallback that has never been tested is a comforting string in a config file, not resilience.

Keep prompts, tool schemas, and output contracts versioned independently of provider consoles.

Own your operational history

Retain the request metadata and business outcomes needed to compare providers and investigate incidents. Exportability matters because provider dashboards use different names, windows, and cost models.

Review portability before adopting fine-tunes, proprietary agents, or hosted memory. The feature may still be worth it; the dependency should be a conscious trade.

From the team that builds it

Where this shows up in INFRO

INFRO is a control plane in front of the provider accounts you already hold. The capabilities below are the parts of it this article touches, each with the documentation that defines its behaviour.

  • Text — OpenAI-compatible

    Available with a plan

    POST /v1/chat/completions with the request shape the OpenAI SDKs already send, including streaming and tool calling.

    Read the documentation for Text — OpenAI-compatible
  • Provider connections

    Available with a plan

    Connect provider accounts you already hold. Each credential is encrypted when saved, scoped to your organization and never shown again; applications use INFRO gateway keys instead.

    Read the documentation for Provider connections
  • Usage, request and FOCUS exports

    Available with a plan

    GET /v1/usage and GET /v1/requests on any gateway key, the request log and usage series as CSV, plus a FOCUS v1.4 Cost and Usage dataset as JSON or CSV, so AI spend lands in your FinOps platform beside the rest of your cloud cost.

    Read the documentation for Usage, request and FOCUS exports

INFRO accounts are self-serve. Provider usage is billed to you by your providers; INFRO charges a software subscription and takes 0% of model spend. See plans.

About this article

Last checked against its sources on . The next review is due by . No separate named reviewer is recorded for this article.

How articles are written, sourced and corrected is set out in the editorial standards.

Revision history

  1. Removed the promotional template sections and the generic FAQ, moved product context into the product section, and corrected product wording to the current BYOK model.