Give your agents
the context
Drop PDFs, spreadsheets, and docs into a vector store, and your agents retrieve the right passages at run time with semantic search. Retrieval-augmented answers grounded in your data, not the model's guesswork.
returns-policy.pdfindexedproduct-catalog.csvindexedsupport-faq.docxindexedreturns-policy.pdf0.94support-faq.docx0.89From documents to grounded answers
Drop in your docs
Add PDFs, spreadsheets, and documents to a collection. No pipeline to build and no embeddings to manage by hand.
Indexed into a vector store
Spojit chunks and embeds the content into a searchable semantic index, ready for agents to query.
Agents retrieve at run time
During a run, the agent searches the collection and pulls back the passages that actually answer the question.
Retrieval built into the workflow
Semantic search
Agents find passages by meaning, not exact keywords, so they retrieve the right context even when wording differs.
Persistent collections
Keep an ongoing knowledge base that many workflows and runs can query, updated as your documents change.
Transient collections
Spin up a single-run collection that auto-cleans when the workflow finishes. Ideal for one-off invoice and document extraction.
Any format
PDFs, CSVs, spreadsheets, and docs all go in. Parsing the formats is handled, so you just add the files.
Grounded answers
Agents answer from retrieved passages, which cuts hallucination and lets you trace where an answer came from.
Per-workflow scope
Attach the right knowledge to the right workflow, so each automation sees only the context it should.
Context where it counts
Invoice and document extraction
Load a document into a transient collection, pull the fields you need, and let it clean up when the run ends.
Product catalog answers
Let an agent answer questions about your catalog from the real product data, not a stale prompt.
Policy and SOP grounding
Ground decisions in your policies and procedures so the agent follows your rules, not generic ones.
Support knowledge
Answer customer questions from your help content and docs, retrieved fresh on every run.
Retrieval vs stuffing the prompt
Give the model the few passages that matter, not your entire corpus pasted into every call.
Use a knowledge base when
- The answer lives in documents too large to paste into a prompt
- You want answers grounded in your data, with sources
- The knowledge changes and the workflow should use the latest
Without retrieval you
- Paste whole documents into the prompt and hit context limits
- Pay for tokens on text the model does not even need
- Get confident answers that are not actually in your data
Ground your agents in your docs
Start free, add a collection, and let an agent answer from your own data. No card needed.