94% of Support Questions Answered Instantly. Without a Human.

IMPACT

Results

THE PROBLEM

From buried PDFs to instant expert answers

FIRMTECH had gigabytes of technical manuals and 6 months of support chat logs — but support managers still spent 30% of their day answering the same questions from memory. We built a RAG-powered AI agent on n8n that ingests any PDF in 1 minute, retrieves exact answers semantically, and escalates to a human only when confidence is low. Result: 80% of Tier-1 queries automated, 24/7 coverage, zero hallucinations on documented topics.

The Problem: Gigabytes of Data, Zero Answers

FIRMTECH had everything documented — technical PDFs, product manuals, support transcripts. The information existed, but it wasn't accessible. Finding an answer required digging through folders, cross-referencing specs, or relying on whoever happened to remember a past support case.

Support managers were drowning. They spent 30% of working hours answering the same repetitive Tier-1 questions that were already documented somewhere. Clients waited. Errors crept in. And at 3 AM, there was nobody to ask.

Standard chatbots "hallucinate" answers when they don't know something. FIRMTECH needed a system that only answers from verified internal documentation — or flags a human agent when it can't.

HOW IT WORKS

RAG Architecture: Retrieval Before Generation

Instead of training a model on company data (expensive, slow, stale), we built a Retrieval-Augmented Generation system. The AI always searches the actual documentation first, then formulates a response grounded in retrieved context.

If the similarity score between the question and retrieved chunks falls below a threshold, the system immediately alerts a human agent — no guessing, no fabrication.

KNOWLEDGE UPDATES

Zero-Code Knowledge Management via Telegram

We built a custom Admin Panel inside Telegram. To update the bot's knowledge, a manager drops a new PDF into the chat. n8n picks it up, chunks the text, generates embeddings, and upserts into Pinecone. The entire process takes under 60 seconds — no developer, no deployment, no downtime.

TECH STACK

Tools Used in This Deployment

BOTTOM LINE

Your company's knowledge is gathering dust. Let's change that.

We build custom RAG systems that turn your documentation, manuals, and support history into a 24/7 AI consultant — deployed in 2–3 weeks.

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Frequently Asked Questions

What types of data can the AI consultant be trained on?

A retrieval-augmented knowledge base built from your company's own documents — SOPs, past project reports, product specs, emails, and support tickets. When a client or employee asks a question, the AI retrieves the most relevant internal documents first, then answers using that specific context rather than generic training data.

Which file formats does the system support?

PDF, DOCX, XLSX, HTML pages, Notion exports, and plain text files. The system chunks and embeds each document into a PostgreSQL vector store (pgvector). New documents added to the designated folder are automatically indexed via a scheduled n8n workflow — no manual re-indexing required.

What were the results for FIRMTECH in the first month?

The system correctly resolved 94% of incoming support queries without human escalation in the first month. The remaining 6% were automatically routed to a human agent with the relevant source documents pre-attached, reducing resolution time by 65% even on escalated cases.

What happens when the AI doesn't know the answer?

It explicitly states it doesn't have that information — no hallucination, no guessing. The query routes automatically to a human agent via Telegram with the original question attached. This is by design: the system is built to recognize the boundary of its knowledge and escalate cleanly rather than answer incorrectly.

What does deployment cost?

Deployments with document ingestion, vector search, and Telegram interface start at $2,000. More complex systems with multi-language support, approval workflows, or CRM/helpdesk integration range from $3,500 to $5,000. All systems are self-hosted — your documents never leave your infrastructure.