AI Integration · San Francisco, California
AI integration into the systems you already run.
We connect AI to your existing products, APIs, and internal tools — LLMs, computer vision, and predictive models — with the evals, guardrails, and observability to run them safely in production.
What it means
AI that plugs into your stack, not a rip-and-replace.
You do not need a new platform; you need AI inside the systems you already run. We integrate models into your products, APIs, and internal tools — handling the unglamorous parts: authentication, rate limits, fallbacks, evals, guardrails, and the observability to see what the model is actually doing.
We have done this integration work across our own products, from CodeMouse's GitHub-native AI reviews to log.fail's automated incident summaries — so the seams are clean and the failure modes are handled.
Building something net-new on top of LLMs instead? See LLM development. Need it operated at scale afterwards? See MLOps.
Scope
What AI integration covers.
LLM Integration
Wire LLMs into your apps and workflows with retrieval, guardrails, and graceful fallbacks.
Computer Vision
Integrate detection, classification, and OCR models into your products and pipelines.
Predictive Models
Connect forecasting, scoring, and recommendation models to the surfaces that use them.
APIs & Tooling
Clean service boundaries, SDKs, and internal tools so AI is callable across your stack.
Guardrails & Evals
Input/output guardrails and evaluation so integrated models stay in bounds and on quality.
Observability
Logging, tracing, and metrics for every model call, so you can debug and improve it.
How we work
Three steps, no theatre.
Call
A short scoping call. You describe the problem and constraints; we tell you honestly whether and how AI helps — and whether we are the right team.
Scope
A concrete plan: what we build, how we measure it, the timeline, and the path to production. No open-ended retainers dressed up as strategy.
Ship
We build, evaluate, and deploy — then hand over a running system with the monitoring and docs to operate it. We can keep running it if you want us to.
FAQ
Questions, answered.
What are AI integration services?
They are the work of connecting AI models — LLMs, computer vision, predictive models — into your existing products, APIs, and internal tools, including the guardrails, fallbacks, and observability needed to run them safely.
Can you integrate AI without replacing our current systems?
Yes — that is the point. We add AI inside the systems you already run rather than forcing a new platform, with clean service boundaries so it is maintainable.
What kinds of models do you integrate?
LLMs, computer vision models, and predictive/ML models — whatever fits the job — connected to the product surfaces and APIs that need them.
How do you keep integrated AI reliable?
With input and output guardrails, evaluation harnesses, sensible fallbacks, and full observability on every model call so failures are visible and recoverable.
How do we get started?
Email info@squidcode.com describing your systems and what you want AI to do. We will reply with next steps and a scoping call.
More services
Related AI consulting services.
Ready to put AI inside your product?
Tell us what you are building. You will hear back from an engineer, not a funnel.
info@squidcode.com