Knowledge base
Precision-engineered RAG engine that eliminates loops and powers accurate AI responses through contextual understanding.
Connect documents, URLs, and databases. PDFs from legal, help docs from your site, product specs from Notion. Our chunking algorithm preserves semantic meaning and keeps related concepts together. A paragraph about your refund policy doesn't get split mid-sentence.
Every knowledge chunk gets converted into vector embeddings that capture semantic meaning, not just words. "Money-back guarantee" and "refund policy" become mathematically similar, even if they share zero keywords. We map relationships between concepts across your entire Knowledge Base so product features connect to billing policies, and troubleshooting steps link to technical requirements.
The system conducts vector similarity search across millions of chunks, combined with keyword signals, recency weighting, and source authority. Technical queries prioritize exact terminology. Policy questions favor the latest approved version.
Initial retrieval casts a wide net. Re-ranking refines it using a secondary model to evaluate relevance in the context of the actual query. We then assemble retrieved content in logical order with enough surrounding context to generate coherent answers. The LLM generates responses using only the retrieved context. No speculation. No fabrication.
In our AI Evaluation section, we score retrieval confidence based on semantic similarity, source authority, and content completeness. Based on a synthesized data set, we validate the answers against the retrieved chunks. This validation layer means you can actually trust your AI Agents enough to deploy them. Test queries against your Knowledge Base, see confidence scores in real time, and set guardrails before going live.
Track complete conversation threads, resolution rates, and sentiment analysis to identify patterns in how your AI Agents perform. We surface knowledge gaps, highlight where retrieval confidence is low, and show you which topics need better documentation. When you update your Knowledge Base, changes sync automatically with your AI Agents in real time. No redeployment, no version lag. Your system gets smarter with every conversation, and you have full visibility into that evolution.
Helps citizens report municipal service issues like potholes, graffiti, and missed trash collection by creating official work orders for city crews. It also provides status updates and general information about city services.
Helps employees find guidance on IT issues and provides troubleshooting steps. If the issue is unresolved, it raises a ticket for IT support.
Sits at your hospital entrance to help patients find the right specialist and room number based on symptoms, providing step-by-step directions and reducing front desk inquiries.
Educates on plans, services, pricing, and perks, then collects user data and takes the user to a placeholder payment gateway once they have chosen a service.
Educates customers about credit card options through targeted questions about their credit situation and spending habits, then recommends the best-fit product with detailed reward calculations and application guidance.
Collects customer information and problem details to provide accurate cost estimates for plumbing, electrical, and HVAC services, then creates work orders for expert callbacks.
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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
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