Integration into your systems
We connect foundation models to the data, APIs, and internal tools a business already runs, with retrieval and grounding so answers are based on real, current information.
Flagship division of AI Depo
Wire AI into production with Interlink LLMOps.
Interlink is the core of what AI Depo does. We connect foundation models to the systems and data a business already runs, then put real operational machinery around them: model routing, evaluation, observability, and version control. The result is AI that ships, holds up under load, and can be changed safely instead of a demo that never leaves the lab.
// routing · evaluation · observability · version control
WHAT INTERLINK DOES
Foundation models, wired into the way a business runs.
A model on its own is not a product. Interlink takes the model and connects it to the systems, data, and tools a business depends on, then wraps it in the operations that let it run reliably in production. This is the flagship lane of AI Depo and the foundation under everything else the depot builds.
Routing across models
Requests are routed to the right model for the job by cost, latency, and capability, with fallback paths so a single provider outage does not take the feature down.
Evaluation and observability
Outputs are scored against evaluation suites before release, and every call is traced for prompts, tokens, latency, and cost so behavior in production is visible rather than guessed at.
HOW IT WORKS
One pipeline from request to production.
Interlink puts a managed path between a request and a model. Input is grounded against your data, routed to the right model, scored, traced, and version-controlled, so what reaches users is intentional and what changed is always knowable.
Ground
We connect the model to your data through retrieval so responses are based on current, real context rather than only what the model was trained on.
Route and evaluate
Each request goes to the right model and tools for the task, and outputs are scored against evaluation suites so quality is measured, not assumed, before release.
Observe and version
Every call is traced for prompts, tokens, latency, and cost, and prompts and configuration are version controlled so changes can be reviewed, shipped, and rolled back.
WHY IT MATTERS
The gap between a demo and a dependable feature.
Plenty of teams can get a model to answer a question in a notebook. The hard part is making it dependable: grounded in real data, routed sensibly, measured against a standard, observable when something drifts, and safe to change. Interlink is the lane that closes that gap, which is why it sits at the center of AI Depo.
- GROUNDED Retrieval ties answers to your real, current data instead of leaving the model to work from training alone.
- ROUTED Traffic is sent to the right model by cost, latency, and capability, with fallbacks so one provider outage is not an outage for you.
- EVALUATED Evaluation suites score outputs against a standard so a release is a decision backed by evidence.
- OBSERVABLE Tracing and version control make production behavior visible and every prompt and config change reversible.
THE CORE LANE
Interlink is the flagship of AI Depo.
AI Depo is the depot where businesses come to get intelligent software built, integrated, deployed, and operated. Interlink LLMOps is its core lane: the model integration and operations that the agents, data, security, websites, and managed deployment the depot runs are all built on top of.
START A PROJECT
Have a model you need to get into production?
Whether you are starting from a prototype or trying to make an AI feature dependable enough to trust, Interlink wires the model into your systems and puts the operations around it. Tell us what you are building and we will scope it with you.