01
Understands what you sell
The catalogue is read and indexed first, so targeting follows the products themselves rather than a keyword the operator guessed.
AIMulti-Agent · RAG
AI sales intelligence
Six agents between
a market and a warm reply.
An AI-native B2B sales-intelligence platform. A multi-agent pipeline understands the products, targets manufacturers by city and industry, qualifies them, detects buying signals, and drafts personalised outreach for human approval, engineered so a wrong-company or fabricated lead never slips through.
A pipeline, not a prompt
Each stage has one job and hands on a checked result. Anything the pipeline cannot ground in retrieved evidence is dropped rather than invented, because a plausible wrong company costs more than a missing one.
6
Agent Stages
Fail-safe
Guardrails
RAG
Grounded
01 · Understand the product catalogue
02 · Target by city and industry
03 · Enrich and verify the company
04 · Qualify and score the fit
05 · Detect buying signals
06 · Draft outreach for approval
What it does
Targeting that can be checked.
The platform is built around the assumption that any claim it makes will be read by the person whose name goes on the email.
02
Targets by city and industry
Manufacturers are sourced against an explicit geography and sector brief, which keeps the list reviewable and the reasoning visible.
03
Qualifies before it scores
Fit is assessed on retrieved evidence about the company, and the score carries the reasons behind it rather than a bare number.
04
Detects buying signals
Signals that suggest a company is in the market now are surfaced alongside the fit, so sequencing is a decision, not a guess.
05
Drafts, never sends
Outreach is written personally to the company and queued for human approval. The system prepares the message; a person still sends it.
06
Guardrails that fail safe
A lead that cannot be grounded in retrieved sources is discarded. No fabricated company, contact or claim reaches the queue.
How it is built
Retrieval first, generation second.
Python
FastAPI
Multi-Agent Orchestration
RAG
Embeddings
Vector DB
PostgreSQL
Docker
Let's build
Need a pipeline like this one?
Tell us about the hard problem. We'll show you how we'd architect, build and ship it.