Needle
Needle turns your documents into a searchable knowledge layer. Your Tars AI agent performs semantic search across PDFs, docs, and files in real time, finding the exact answer buried in your data. Customers get precise, source-backed responses instead of generic replies.
Your AI agent manages document collections and runs semantic search queries through Needle, delivering precise, source-referenced answers from your own knowledge base.
Needle
Watch how support teams, product organizations, and research departments use AI agents to unlock answers from their document repositories through natural dialogue.
A developer asks your support chat how to configure webhook retries. Your AI Agent searches the Needle collection containing your API documentation, finds the relevant section with code examples, and presents the answer with a link to the source page. The developer gets their answer in seconds instead of searching through a 200-page doc site.
An employee asks about parental leave eligibility. Your AI Agent performs a semantic search across your HR policy collection in Needle, retrieves the specific policy section including eligibility criteria, duration, and application process, and presents it with the document reference. HR handles fewer repetitive questions.
A prospect asks how your enterprise plan differs from the professional tier. Your AI Agent searches your pricing and feature documentation in Needle, extracts the relevant comparison points, and presents a clear feature-by-feature breakdown. The prospect gets a data-backed comparison during the sales conversation.
Needle
FAQs
Needle indexes PDFs, DOCX, XLSX, plain text files, and more. When documents are uploaded to a collection, Needle automatically chunks, embeds, and indexes the content for semantic retrieval. The agent can search across all indexed file types in a single query.
Keyword search matches exact terms. Needle's semantic search understands meaning, so a query about 'return policy' finds relevant content even if the document says 'refund guidelines' or 'product exchange process.' This means the agent finds answers that keyword search would miss.
Yes. Needle returns source references with every search result, including the file name and the specific passage that matched. The agent presents these citations in its response, and can generate a download link for the original document.
No. Documents live in your Needle account. Tars queries Needle's search API in real time and receives text passages and metadata. The original files are never copied to or stored by Tars. You maintain full control over your document repository.
Needle automatically processes and indexes documents after upload. For most file types, content becomes searchable within minutes. Large documents or bulk uploads may take slightly longer. The agent can check collection stats to confirm indexing is complete.
Yes. When configuring the agent in Tars, you specify which Needle collection IDs the agent can query. You can restrict customer-facing agents to public documentation while internal agents search HR policies or engineering docs.
The max_distance parameter controls how strict the relevance threshold is, on a scale from 0 to 1. Lower values return only highly relevant results. Higher values cast a wider net. The agent uses this to balance precision and recall based on the query context.
FAQ pages require users to browse and find the right article. With Needle and Tars, customers ask questions in their own words and get precise answers extracted from your full document library. It handles questions that were never anticipated in a pre-written FAQ.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
Email - sales@hellotars.com
.png)
%201.png)
%201.png)
