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Query understanding
Each question is rewritten and expanded into several targeted searches for full coverage.
Agentic retrieval
Kapa searches in a loop, refining its queries until it has enough evidence to answer.
Grounded answer
Built only from retrieved sources, with inline citations, or an honest “I don’t know.”
Safety & guardrails
Answers only about your product, keeps personal data private, refuses anything unsafe.
RESEARCH
Better answers start with better context
more accurate retrieval than DIY and off–the–shelf RAG
The gain comes from agentic, multi-pass retrieval.
Continuous evals
Offline and online, every change proven before it ships.
A dedicated AI research team
Its only job is accuracy, across every new model and technique.
30M+ answers, hardened in production
That volume lets us A/B test every change to significance.
READ THE RESEARCH
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Says “I dont know” instead of guessing
When your sources lack the answer, Kapa says so and logs the gap to fill next.
References its sources
Linked sources on every answer, verifiable in one click.
Answers in your language
Kapa replies in any language, grounded in your sources.
Stays inside your knowledge domain
Kapa will behave like a product expert, not a general chatbot.
SOC 2 Type II
Independently audited and
compliant with SOC 2 Type II.
SOC 2
GDPR Compliant
Compliant with EU data
privacy regulations.
GDPR
SSO & RBAC
Single sign-on and
role-based access control.
Zero Data Retention & PII Masking
Detect and mask sensitive data
before processing.
Get a free trial
Test and evaluate Kapa for free
Go live in less than 7 days
SOC 2 Type II & GDPR compliant
How accurate is Kapa, and how do you prevent hallucinations?
Kapa is a retrieval-augmented (RAG) system: it retrieves from your trusted sources before generating an answer, using domain-specific retrieval and state-of-the-art techniques to minimize hallucinations. On retrieval benchmarks, it scores about 2X higher than web search APIs and DIY RAG pipelines.
What happens when Kapa doesn't know the answer?
It tells you. When the sources don't sufficiently cover a question, Kapa marks the answer as uncertain and says something like "I do not have enough information" rather than guess. Those uncertain responses are then surfaced as coverage gaps so you know what to add.
How do I know an answer is trustworthy?
Every answer is grounded in retrieved sources and cites them inline, so your users can verify the answer in one click and you always know where it came from.
Which AI models does Kapa use?
Kapa is model-agnostic, not tied to any single model or provider. It works across OpenAI, Anthropic, Cohere, Voyage, and its own models, selecting the best-performing one for each use case, with DPAs and training opt-outs in place at every provider.
How is Kapa different from ChatGPT or Claude?
ChatGPT and Claude are general-purpose LLMs that answers from its training data. Kapa retrieves from your trusted sources first and is purpose-built for technical questions, so answers are accurate, current, and specific to your product.
Does Kapa answer from the open internet?
No. Kapa answers only from your connected sources, not from whatever the model absorbed online. That's the difference between an agent that knows your product and one that invents things you've never built.
How does Kapa keep getting more accurate over time?
A dedicated research team continuously evaluates new models, research, and techniques against offline and online evals, and automatically adopts whatever improves accuracy. You stay on the most capable version with no work on your side.
Can Kapa answer accurately in other languages?
Yes. A user can ask in French, Mandarin, or another language and get a correct answer drawn from your English sources. The question and your content don't have to be in the same language.