Build AI agents that actually understand your revenue data.
Your agents don't carry a quota.
Designed for RevOps teams engineered revenue:
Prove what your AI agents closed.
Close the loop between agent and seller action → revenue. Every action is traced and joined back to the deal it moved, so you can show what your AI actually drove.
Cut AI token spend.
Serve up the right, pre-enriched context instead of raw data on every call. Agents use up to 70% fewer tokens — and produce sharper, grounded output.
Context for every agent.
Build a central context layer, delivered to every seller and agent in a single MCP call. One endpoint, any model, no lock-in.
Build your own sales agent.
Ship a fully-configured and customized AI assistant today — white-labeled, trained on your data, proactive on at-risk deals, and observable in your Loop console.
Build a private AI model, trained on your revenue data.
Serve pre-enriched context once and reuse it across every agent. Teams cut token use up to 70%.
Revenue teams shipping AI that earns its seat.
AI for RevOps is the practice of giving AI agents and sellers a structured, revenue-aware context layer so they make decisions grounded in what actually drives deals to close. Instead of generic CRM dumps, Fluint trains a private model on your GTM data, captures which agent and seller actions correlate with wins, and serves that judgment-enriched context to every agent, tool, and rep over a single MCP call.
Most observability tools only show that an agent ran and what tools it called. Fluint Loop traces every agent and seller action across the full sales cycle and joins it back to revenue outcomes — closed-won, ACV, cycle time, and win rate — so you can prove which AI activity actually moved deals and why.
Yes. Fluint trains org-scoped models with private weights. Your data is never shared with other customers or used to train models for other organizations. Your model, context, and outputs are private to your org.
A context layer pre-materializes judgment-enriched context once, then serves it to every agent on request. Agents no longer re-reason over raw CRM data and transcripts on every call, so they consume up to 70% fewer tokens while producing more grounded output.
MCP (Model Context Protocol) is an open standard that lets any AI agent request context through a single endpoint. Fluint delivers your revenue context layer over MCP, so Claude, OpenAI, Glean, Copilot, and custom agents all read the same judgment-enriched context the same way — with no proprietary SDK and no vendor lock-in.
Yes. Fluint Chat is a fully configured, white-labeled AI sales assistant trained on your data. It proactively prompts reps, runs 30+ selling workflows, writes back to your CRM, and is fully observable inside the Loop console — with no engineering team required to launch it.
Put your revenue data to work — for every agent and seller.
without building it themselves.