What is a knowledge base?
In VectorGap, your knowledge base is the authoritative source of truth about your brand.
When AI makes a claim about your company, we compare it against your knowledge base. Matches are accurate. Mismatches are potential hallucinations.
The more comprehensive your knowledge base, the better we can assess AI accuracy and identify what needs correction.
Essential information to include
Start with facts AI commonly gets wrong:
Company basics - Founded date, headquarters, employee count, funding
Product information - Features, pricing, integrations, limitations
Customer facts - Number of customers, notable logos (with permission), industries served
Competitive positioning - What you compete with, key differentiators
Team - Founders, executives, key hires (public information only)
Timeline - Major milestones, product launches, pivots
Document structure best practices
Format documents for easy extraction:
Use clear headings - "Pricing Plans" not "Our Value Proposition"
State facts directly - "Starter plan: €49/month" not "affordable plans available"
One topic per document - Easier to update and process
Include dates - "As of January 2024, we serve 10,000 customers"
Avoid marketing language - Facts only, no superlatives
Sourcing accurate information
Pull from authoritative internal sources:
Product documentation (current version)
Pricing pages (verify with finance)
Press releases (factual content only)
Annual reports or investor materials
Legal filings (if public company)
Don't upload: Marketing collateral with soft claims, outdated documents, speculative content.
Handling sensitive information
Your knowledge base is used for comparison, not shared publicly.
Safe to include: Public pricing, announced features, published customer counts
Be careful with: Unreleased products, internal metrics, customer names without permission
Never include: Customer data, credentials, trade secrets
When in doubt, include only information you'd put in a press release.
Maintenance schedule
Outdated knowledge bases create false accuracy signals. Update:
Immediately - Pricing changes, new products, acquisitions
Monthly - Customer counts, employee numbers, feature additions
Quarterly - Full review of all documents
Annually - Major refresh with all current information
Set calendar reminders. An outdated knowledge base is worse than no knowledge base.
Internal truth is not enough
A knowledge base is valuable because it tells your team what should be true. But AI systems need public, crawlable confirmation to repeat that truth.
Use the knowledge base as the control plane, then push important facts into public pages, docs, FAQs, schema, and trusted external profiles.
What to include
Include canonical facts, retired facts, proof links, acceptable wording, forbidden claims, competitor boundaries, pricing truth, market scope, and source URLs.
Version the facts. When an AI answer is wrong, you need to know whether the public site is stale, the model is stale, or your own source of truth is unclear.