Ingest PDFs, web pages, Q&A pairs and more. AI extracts knowledge, creates vector embeddings and makes everything semantically searchable.
99%
Retrieval accuracy
<200ms
Search latency
3072-dim
Vector embeddings
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Every article, Q&A pair, and document is automatically chunked, embedded, and stored in a vector database. The right information surfaces at the right moment — whether it's an AI reply or a team member searching for an answer.
3,072
Vector dimensions
OpenAI-compatible embeddings
∞
Collections
Organize by product, team, or channel
< 1s
Semantic search
Cosine similarity via pgvector
100%
Your data
You own it — no vendor lock-in
product-manual.pdf
2.4 MB · 142 chunks embedded
api-reference.md
340 KB · Embedding chunks…
https://docs.acme.io
12 pgs · Fetching & parsing…
faq-export.csv
88 KB · Queued
Simple by design
No complex setup. No integrations maze. Just four steps from zero to AI-powered support.
Import Q&A pairs, paste web URLs, or upload documents. Mindmore chunks and embeds everything automatically.
Hook up your support email via IMAP or create an API channel for your product. Tickets start flowing in.
When a ticket arrives, AI searches your knowledge base and drafts a reply — grounded in your actual content.
Review the suggestion, tweak if needed, send. Every resolved ticket can be saved back to your KB automatically.
Content types
Mindmore handles structured and unstructured content. Upload once, search forever.
Upload PDF, Word and text files. AI extracts Q&A pairs and creates chunks automatically.
Import any URL or sitemap. Pages are fetched, cleaned and kept in sync.
Write or import question-and-answer pairs directly. Perfect for FAQs and support scripts.
Vector search finds conceptually related content, not just keyword matches.
Content is split into optimal chunks with metadata preserved for accurate retrieval.
Link collections to helpdesk channels so AI suggestions are always contextual.
Get started in minutes. No credit card required.