ABP product · BPMDoc

SmartSearcher

Enterprise search and answers over your documents — with sources, without made-up facts.

Ask a question in natural language — the system finds relevant fragments in your corporate corpus, re-ranks them, and builds an answer with citations: not only the document, but the exact page. Clicking a source opens the PDF positioned on that page. The pipeline is orchestrated by a multi-agent core.

Built by ABP. The SmartSearcher product.

In one environment

  • Hybrid search + re-rank
  • Answers only from retrieved documents
  • Source down to PDF page, open with position
  • Out-of-the-box integrations (Confluence and more)
  • Local login or Keycloak / SSO
  • ACL from data sources
  • Multi-agent pipeline orchestration

Product in action

SmartSearcher UI: knowledge sections and search with answers and sources. Browse the screens or click a shot to open it large.

Company knowledge exists. Finding it is hard.

A typical picture that enterprise search and RAG platforms address: knowledge is scattered, public models do not know your environment, and documents must not leave the perimeter.

Documents in many places

Policies, instructions, mail, project materials — employees waste time on manual search or “asking a colleague”.

Public AI is not enough

A cloud model does not know your standards and internal rules and must not receive confidential corporate data.

Answers need evidence

For engineering and regulations, a confident paragraph is not enough — you need an answer grounded in a specific document fragment.

How it works

A full RAG pipeline: from file upload to an answer with links. Each stage is a dedicated pipeline agent under a single core.

01

Ingest

Documents land in object storage. Indexing jobs go to a queue.

02

Index

Parsing, chunking, embeddings, write to vector store and metadata.

03

Hybrid search

Semantic, lexical, and full-text channels with fusion ranking.

04

Answer with sources

Re-rank → context assembly → LLM generation. The answer cites document and page; a click opens the PDF on that page. No fragments — an honest refusal.

Multi-agent orchestration

SmartSearcher is not “one script on top of an LLM”, but a set of specialized agents. The core coordinates ingest, retrieval, ranking, and generation, routes requests to topical assistants, and performs tool calling during the dialogue.

What is implemented

  • Ingest and indexing agent
  • Hybrid retrieval agent
  • Ranking agent (cross-encoder)
  • Answer generation agent with citations
  • Topical assistants and request routing
  • Tool calling from the dialogue

Capabilities

Grounded answers

Answers are built only from retrieved fragments. No source — no invented fact.

Hybrid search

Dense + sparse + FTS: catches both meaning and exact codes, identifiers, and designations.

Citations to the page

The system points not only to the document, but to the relevant page. Clicking a source opens the PDF positioned on that page — no manual scrolling.

Async processing

Indexing via queue and workers — uploads do not block user dialogue.

Web UI

Search, document management, knowledge sections, indexing statuses.

Customer perimeter

Docker Compose or Kubernetes. Images can be delivered for air-gapped deployment.

Integrations, auth, and access

Enterprise setup: connect corporate systems out of the box, familiar employee login, and permissions aligned with knowledge sources.

Corporate systems out of the box

Integration with corporate information systems — for example, Confluence — without a custom connector build for every pilot. Knowledge sources plug into the product runtime.

User authentication

Sign in locally (SmartSearcher accounts) or via corporate identity — for example, Keycloak / SSO. One access point for customer employees.

Access control and source ACL

Role model and view restrictions on materials. Access control integrates with data sources — for example, Confluence restrictions: users only see in search what they already may see in the source.

Security and deployment

Data stays with you

  • Deployed in your internal environment
  • Documents in object storage on your infrastructure
  • Local auth or Keycloak / corporate IdP
  • ACL and inherited restrictions from sources (Confluence, etc.)
  • Action logging

Delivery options

  • Standalone: Docker Engine + Compose
  • Production: Kubernetes, image registry
  • LLM in a private scenario (incl. GigaChat)
  • Scaling of indexing workers

Technology stack

API

Python, Litestar (async)

UI

Next.js, React, TypeScript

Search

Qdrant, PostgreSQL FTS, re-ranker

Queue

RabbitMQ, async workers

Storage

MinIO, PostgreSQL, Redis

Auth & IdP

Local accounts, Keycloak / OIDC

Integrations

Confluence and corporate systems

Platform

Docker, Kubernetes

Product status

SmartSearcher is an ABP product (BPMDoc brand). It is a full-featured enterprise RAG / multi-agent knowledge search solution.

The product is intended for pilots and production in the customer’s environment: corpus ingest, indexing, hybrid search, answers with sources, container deployment.

Ready to show it on your documents

Tell us about your knowledge corpus and environment — we will propose a pilot architecture and a SmartSearcher rollout plan.