Overview
Most enterprise knowledge is locked in formats that defeat AI — poorly structured documents, disconnected systems, inconsistent taxonomies, and data quality issues that make retrieval unreliable. A well-designed knowledge base is the foundation that determines whether your AI systems produce trustworthy answers or hallucinate. We design, build, and maintain knowledge bases optimised for AI retrieval — combining document architecture, metadata design, vector storage, and ongoing curation processes that keep your knowledge current and your AI grounded.
How It Works with a21
Knowledge Audit & Architecture Design
Inventory your knowledge sources — documents, databases, wikis, emails, systems. Assess quality, currency, and accessibility. Design the knowledge base architecture including storage, structure, and metadata schema.
Ingestion Pipeline & Indexing
Build automated ingestion pipelines that extract, preprocess, chunk, and index content from all source systems. Implement quality controls that flag and route low-quality content for review.
Ongoing Curation & Governance
Establish the processes, tooling, and ownership model for keeping the knowledge base current — including update workflows, quality monitoring, and content lifecycle management.
What We Offer
Knowledge Architecture Design
Design the taxonomies, metadata schemas, and structural conventions that make knowledge findable and contextually meaningful for AI retrieval.
Multi-Source Ingestion
Build pipelines that ingest and harmonise content from diverse sources — SharePoint, Confluence, PDFs, databases, email, structured data — into a unified knowledge store.
Vector & Semantic Indexing
Index knowledge using both vector embeddings and structured metadata — enabling semantic search, keyword search, and filtered retrieval.
Content Quality Management
Implement quality scoring, duplicate detection, and staleness monitoring — ensuring the knowledge base remains accurate, current, and trustworthy.
Access Control & Permissioning
Implement knowledge-level access controls that ensure AI only surfaces content the querying user is authorised to see.
Knowledge Governance Workflows
Design the ownership, review, and update workflows that keep knowledge current — embedding knowledge curation into your existing content processes.
Why Choose a21
AI-Optimised, Not Just Stored
We design knowledge bases specifically for AI retrieval — not just document management. Structure, chunking, and metadata are optimised for what makes RAG systems accurate.
Curation-First
We treat knowledge quality as an ongoing operational responsibility, not a one-time project. We design governance processes that maintain quality over time.
Enterprise Scale
We build knowledge bases that handle millions of documents, complex permission structures, and high-throughput retrieval without performance degradation.
Source Agnostic
We ingest from wherever your knowledge lives — SharePoint, Confluence, S3, databases, email — through standardised pipelines with consistent quality controls.
Success Stories
Problem
A global law firm had 20 years of legal opinions, precedents, and research scattered across SharePoint sites, email archives, and local drives — inaccessible to both lawyers and AI systems.
Solution
Designed a unified knowledge base architecture, built ingestion pipelines from eight source systems, implemented vector and keyword indexing, and established a knowledge governance process.
Problem
A pharma company’s regulatory affairs team had no structured way to access precedent submissions, agency guidance, and internal SOPs — causing redundant research and inconsistent submissions.
Solution
Built a regulatory knowledge base covering 15,000 documents with metadata schema, permission controls by product and region, and a curation workflow for regulatory updates.
Tech Stack & Tools
Pinecone / Weaviate / pgvector
Unstructured.io / Azure Document Intelligence
LlamaIndex / LangChain
Elasticsearch
Apache Airflow
SharePoint / Confluence / S3 connectors
Redis
Get Started
Build the knowledge foundation your AI needs to be reliable. Talk to a21 about knowledge base design.
