USE CASE 03 · CONTEXT LAYER

Your agents are only as good as the context you feed them.

the gap

Build the context once. Feed it to everything.

Every new agent shouldn't mean re-plumbing context. One layer feeds Claude, your custom agents, and your reps the same way.

Step 1 · Unify

Join your revenue data into one layer.

Loop reads CRM, conversations, emails and enterprise data to join them into a single, unified data schema that's ready for training.

Step 2 · Enrich

Context with judgement, not just data.

A private model trained on your cloed-won history labels what matters, turning raw records into

Sep 3 · Serve

One MCP endpoint, any agent.

Swap models or vendors and the context layer stays put, so every agent you run stays consistent and grounded.

Start free

Run a guided POC

Explore

Where teams start.

Loop

Prove what your AI agents closed

Agent-to-revenue attribution for every action.

View use case

Loop

Cut AI spend

Up to 70% fewer tokens via pre-enriched context.

View use case

Chat

Build your own sales agent

Ship a fully configured, white-labeled AI sales agent your reps trust, live in about a week.

View use case

Loop

Build a private AI model, trained on your reenue data.

Managed private ML, trained on your outcomes.

View use case

Ai for revops

See all use cases

Questions about AI
for RevOps.

Fundamentals

What is AI for RevOps?

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

How do I measure whether AI agents impact revenue?

Is my revenue data private?

Context & Cost

How does a context layer reduce AI token spend?

What is MCP and why does it matter for revenue teams

Can I buy a fully managed AI sales agent instead of building one?

Get Started

Give every agent context worth reading.

Start free, connect your stack, and serve enriched context to your first agent the same session.

Start free

Build your assistant

Your agents are only as good as the context you feed them.

Build the context once. Feed it to everything.

Join your revenue data into one layer.

Context with judgement, not just data.

One MCP endpoint, any agent.

Where teams start.

Prove what your AI agents closed

Cut AI spend

Build your own sales agent

Build a private AI model, trained on your reenue data.

Questions about AIfor RevOps.

Give every agent context worth reading.

Questions about AI
for RevOps.