MaxKB

MaxKB features and use cases

Knowledge retrieval, agents, workflows, models and integrations for enterprise AI.

Deploy in controlled infrastructure

MaxKB can run on premises or in a private cloud and connect to local, hosted or external language models. This lets the organisation balance confidentiality, response quality, latency and infrastructure cost.

Build knowledge bases

Upload documents or collect approved web pages. The platform extracts text, splits it into searchable fragments, calculates vector representations and retrieves passages by meaning rather than exact keywords.

Ground answers with RAG

Retrieved passages are supplied to the model as controlled context. Prompts, retrieval thresholds, citations and fallback behaviour can be tuned and tested against representative questions.

Use multiple knowledge sources

One application can query several knowledge bases. Access boundaries can separate departments, products, customers or confidentiality levels.

Create AI applications and workflows

Visual workflows combine retrieval, model calls, conditions, branches and custom functions. MCP tools and APIs let an agent obtain approved data or invoke a corporate action rather than only generate text.

Integrate and publish

Applications can be exposed through a web chat, embedded into a portal or connected through API to support, learning and business systems. Testing and debugging tools help validate behaviour before publication.

Enterprise rollout

Begin with a bounded knowledge set and measured questions. Then add identity, monitoring, model routing, separate environments and a publication process for multiple teams.

Discuss your scenario

See the product with an AFI engineer

We will agree on the demonstration, PoC criteria or input data for licence and integration cost sizing.