# UnicornIQ’s Vera data fact checker for sales and sales chatbots > Source: > Published: 2026-10-09 17:58:18+00:00 # UnicornIQ’s Vera data fact checker for sales and sales chatbots [UnicornIQ](https://unicorniq.ai/)’s Vera technology tech is designed to prevent AI hallucinations when working with enterprise data. Vera bills itself as a "verified intelligence platform" “that makes AI tell the truth.” The aim is to find old data, like product prices, that conflicts with newer data, and replace the old with the new so that a sales proposal prepared by a sales chatbot is truthful. Vera is designed to act behind or as an AI chatbot and has two components: a data ingestor and a natural language-fed query answer facility. The ingestor cleans a company’s unstructured data, including documents, PDFs, slide decks, chats and emails where most knowledge actually lives, before any AI uses it. It breaks unstructured content into individual items, called claims, recognizing the specific facts inside them, such as a price, a spec, a date, sales course, or a policy. It checks each claim against every other claim. Conflicts and outdated facts are resolved, or flagged for an expert (maven) to settle, before AI uses them. A verified claim is said to be "sealed." The query answer part accepts input from a natural language-fed sales chatbot and returns truthful answers from the cleaned data. For example, it could figure out the answer to a question like “What’s the list price for a 6-unit Kinetic site with Halo and Sentinel Enterprise? The customer’s last quote came off the FY26 price book. Does that price still stand?” Mark Snow, Unicorn co-founder and CTO, said: “For 30 years I was the engineer in the room when the customer asked the hard question, and for 15 years I helped teach the engineers in those rooms for Cisco’s partners. Again and again, we watched good people lose deals because they were working from bad data, or because a new feature already did what the customer needed and nobody knew it existed yet. Our team built Vera so the right answer shows up with the source attached, and so the people who know the most get to spend their time lifting up the next person.” UnicornIQ explains in its press materials, "tech OEMs and VARs suffer from a brutal reality: a field rep has a customer meeting tomorrow morning, so they scramble through a maze of shared drives and outdated portals to duct-tape together a pitch. They end up quoting old pricing, referencing discontinued product features, or missing context on what the specific customer bought last quarter." It says generative AI promised to fix this, but when a model doesn’t know something it fills the gap with an answer that sounds right. Retrieval-augmented generation (RAG), the standard fix, searches a company’s documents but never checks whether they agree with each other or are still true. Users are then presented back with whatever answer the AI decided was correct that day. Specific subfeatures of Vera include: - **An a****utonomous enablement engine** stops the field from pitching blind off outdated PDFs. Vera tracks live product changes and automatically updates learning paths, coaching materials, and documentation in real time so your field is always selling the current reality.*“Vera, how do I pitch this new feature to ACME Corp? Build me a compliant leave-behind leveraging current pricing and our latest company brand guidelines.”*  - **A** **full channel partner program** **is billed as a** complete operational layer built for the channel ecosystem. Vera handles partner records, contracting, deal registration and attribution, tiers, rebates, and incentives, actively orchestrating the entire partner lifecycle. - **A** **CRM & execution Layer** works alongside enterprise systems like Salesforce rather than replacing them. Vera surfaces stale deals, flags missed touch points, and runs scheduled actions like drafting replies, turning static knowledge into active revenue generation. - **Pitch coaching & accuracy auditing** **lets reps** practice pitches inside of Vera or ask Vera to sit in on live customer meetings. Vera actively evaluates them not just for delivery habits, but for product and pricing accuracy against the verified knowledge base. Vera is available now. Access the free [demo trial](https://v3r4.ai/try?world=sirdar&audience=channel&site=apex&variant=a) or contact sales/partnership teams at unicorniq.ai.  ##### Comment UnicornIQ does not say Vera is an AI chatbot or large language model (LLM), but departed co-founder [Joe Onisick](https://www.linkedin.com/in/joeonisick/) implies quite strongly that it is an LLM in its own right. We have asked the company to clarify this. In a February 2026 YouTube [video](https://youtu.be/bhGFWTpt27A) Onisick likens Vera to a data hygiene black box, speaking of how Vera looks at data sources: “I can parse them and distill the information, and then I create a vector database which is just a source of truth. It’s not really metadata about your data. It’s the facts in text with a vector index in a gravity-weighted database.” That sounds like an LLM. The data is exposed via an API and MCP (Model Context Protocol) server. Vera is designed to fit in with whatever AI stack a customer has and “sit in the back," for example, behind a sales AP chatbot. So, Onisick says: “Just add a prompt to that existing agent and tell it to check for truth first.” Then the chatbot agent connects to Vera to use its information. If Vera gets asked a question it can’t answer, than it says so and requests a human maven, a trusted specialist, to provide an answer in a human-in-the-loop exercise. A maven-supplied answer is then added in to Vera’s knowledge base and used from then on. ##### **Bootnote** [Icertis](https://www.icertis.com/company/) and UnicornIQ are not related. Each ship a separate product named Vera, and nothing public links the companies or the products. Icertis Vera is the contract-intelligence layer inside Icertis’s contract lifecycle management platform.