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Case study · B2B services · 2025

AI answers 48x faster than a human.

A B2B SaaS with a heavy stream of tickets. We built a RAG copilot over their knowledge base - handling a request dropped from hours to minutes.

48×
faster handling
90%
of requests resolved without a human
24/7
answers for customers
RAGClaudeagentsVector DB
B2B SaaS — RAG copilot over a knowledge base
Challenge

Where the time was leaking.

The product was growing, and the flow of support and pre-sales tickets grew with it. Every reply meant digging through the docs, the knowledge base and the ticket history.

An agent spent up to 40 minutes on a single non-trivial request: find it, verify it, write it up. The queue kept growing and response-time SLAs were going up in flames.

The search and the first-draft answer had to move to the machine, leaving people the final say.

The pain points

  • Up to 40 minutes on one complex request
  • Knowledge scattered across docs and wikis
  • The queue grew faster than the team could hire
  • Response-time SLAs kept slipping
  • New hires took too long to get up to speed
Solution

What we built.

01

Pulled every request channel (email, chats, phone) into a single amoCRM loop

02

AI parses the spec from an inbound email and drafts the quote

03

Auto-pricing from the price list and live stock levels

01

Indexed the knowledge base and docs into a single vector store

02

Set up RAG search that verifies its sources before answering

03

Claude drafts the answer with citations to the source documents

04

Simple requests close automatically, complex ones go to a human

05

Every answer trains the system further — accuracy keeps climbing

RAGClaudeagentsVector DBPythonAPI
Result

Money in P&L, not model metrics.

48×
faster handling
90%
of requests resolved without a human
24/7
answers for customers

People stay on quality control - the machine handles the grind of searching and drafting.

How it looks
— dashboard screenshot
— funnel screenshot
— call analytics screenshot
Testimonial
"The team was clearing the queue by hand and burning out. Now the copilot closes most requests on its own, and the team works on the things that actually need a brain."
Alexey Volkov
head of support · B2B SaaS
07 · Contact

We'll get the team working while you watch the numbers.

Describe your challenge in two sentences - we'll come back with a plan and a working prototype in 48 hours.

Book a call
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