LAKEer-Search Unstructured Data Reviews & Product Details

Product name: DaaX LAKEer Tagline Verified AI answers from your documents, with citations. LAKEer lets teams ask questions in plain English across PDFs, Office files, email and Teams/Slack, and get answers verified claim by claim against the source documents, with citations and an audit trail. Highest published score on Google DeepMind's FACTS Grounding benchmark. Most AI search tools give one confident answer and leave you to work out which parts are true. LAKEer checks before it answers. It searches your unstructured data (PDFs, Office documents, emails, and Teams and Slack messages), drafts an answer, then breaks it into individual claims and verifies each one against the retrieved sources. Unsupported claims are removed or repaired, and every sentence in the final answer links to the document it came from. LAKEer combines a knowledge graph with vector and keyword retrieval, so it can follow relationships across many documents rather than matching isolated passages. Numbers in tables are calculated deterministically, not guessed by a language model, and every answer comes with an audit trail. On Google DeepMind's FACTS Grounding benchmark, which measures whether AI answers stay faithful to their source documents, LAKEer scored 85.7%, the highest score on their public dataset. Domain knowledge cartridges add industry vocabulary and rules (for example energy/OSDU or e-commerce), and you can upload your own company terminology so answers use your language. Answers are returned in the language of the question. LAKEer runs single-tenant, and your data is not used to train language models. Use it through the Developer Dashboard, or build it into your own applications and AI agents through the REST API or MCP server. Pricing is based on queries and pages, not tokens, so costs are predictable. A free plan is available. Key features Natural-language search across PDFs, Office documents, email, Teams and Slack Claim-by-claim verification of every answer against source documents Citations and source links for every sentence Full audit trail for each answer Knowledge-graph retrieval across multiple documents Deterministic calculations over tables and figures Domain knowledge cartridges and custom company vocabulary Multilingual: answers in the language of the question REST API and MCP server for integration with apps and AI agents Single-tenant deployment; no training of LLMs on customer data Usage and cost reporting Categories Primary: Enterprise Search Software Secondary: Knowledge Management Software; AI / Retrieval-Augmented Generation (RAG); Document Management Typical customers Enterprise knowledge, legal and compliance, operations and engineering teams in regulated or document-heavy industries (energy, financial services, telecom, e-commerce), and developers building AI agents that need grounded answers. Deployment: cloud (single-tenant SaaS); API and MCP access