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ekai raises $1.7MBacked by Misneach and C10 Labs. Yahoo Finance ↗AIA general purpose agent
$1.41MAdded up every order amount, refunds included.
Home / AI agent accuracy
How does ekai drive AI agent accuracy?
AI agents give wrong answers when they don't know what your business terms and metrics mean. ekai builds a shared set of definitions, approved by your experts and checked against your real data, so every AI agent answers consistently and accurately.
AI answers directly now, so nobody catches the mistake.
An analyst used to fix the definition before anyone saw it. Agents removed that step.
Before
QuestionAnalyst checks the definitionAnswer
Now
QuestionNobody checksAgent answers in seconds
Example problem
Ask three AI tools for last quarter's net revenue and you get three numbers.
With nobody checking, every tool works out net revenue its own way.
What was net revenue last quarter?
AIA data agent
$1.29MTook out tax and discounts, then unpaid orders too.
BIYour BI dashboard
$1.36MTook out tax, but kept the discounts in.
$1.32M, the verified answer
$120,000 apart on the same question, and none of them is verified. Each one guessed what net revenue means, because nobody ever wrote it down. Illustrative figures.
The definition was never written down. It lives in your expert's head.
Someone on your team already knows what net revenue means. Watch ekai find the words only they can define, and check each one.
The question"What was net revenue from active customers last quarter?"
"net revenue"Finance
AMOUNT − TAX − DISCOUNT✓Measure rule · expected result 0 violations"active customers"Customer successA completed order in the last 90 days. Trials and returns are out.✓Referential rule · expected result 0 violations
orders marked settled_gwFinanceLegacy payment gateway. Real sales, counted in revenue.✓Measure rule · expected result 0 violations
The verified answer$1.32Mnet of tax and discounts, active customers only✓Defined by Finance and Customer success · 3 declared definitions
Your warehouse calculates the number. AI uses it to answer.
Accuracy comes from keeping the two apart. The calculation is deterministic, the same on every run, and the agent stays probabilistic where it should be: reasoning, explaining and answering in plain language.
Deterministic
Your warehouse calculates
net revenue = amount − tax − discount, the same on every run.
Verified
ekai proves the definition
Every definition can be traced back to the warehouse. Nothing gets shipped unverified.
Probabilistic
AI uses the number
The agent answers $1.32M from Finance's definition, in every tool.
Common questions
Last updated October 28, 2026
How do I enable AI agents with my business context?
Context authored in ekai is pushed out to every AI agent your teams use: general purpose agents, tools and your own custom agents, as well as Snowflake, Databricks and BigQuery agents.
How does ekai drive AI agent accuracy?
ekai gives every AI agent the same verified definition. Your expert authors what each number means, ekai checks the definition against your warehouse before anything ships, and your warehouse calculates the number. The agent uses that number to reason and answer, so it never has to guess the meaning or calculate the number itself.
Why do AI agents give different answers to the same question?
Because the definition behind the number was never written down. Asked for last quarter's net revenue, one tool adds up every order amount, another takes out tax and discounts, and a dashboard keeps the discounts in. Each one guesses what net revenue means, so the answers land $120,000 apart.
Why shouldn't AI agents calculate numbers?
AI is probabilistic, so asked the same question twice it can work out two different numbers. ekai keeps the calculation deterministic: your warehouse calculates every number from a governed definition, the same way every time, and the agent uses that number to reason, explain and answer in plain language.
Who decides what a number means?
The person on your team who already knows. ekai asks your expert only what the data cannot explain, in plain language and grounded in your real tables. Their answer becomes the definition, they are recorded as its author, and nothing goes live until a person on your team has reviewed it.
How do I know an agent's answer is verified?
Every definition can be traced back to the warehouse. ekai runs each check inside your warehouse and reconciles it against facts your experts stated up front. If a check fails, the definition does not go live, so nothing gets shipped unverified, and every answer arrives with its definition and its author.
Which AI agents does ekai work with?
Every agent your teams use. ekai publishes one verified semantic model to general purpose agents such as Claude and ChatGPT, to tools and your own custom agents through ekai MCP, and to Snowflake semantic views and Cortex Agents, Databricks Genie and BigQuery data agents, or dbt MetricFlow for Postgres and Redshift. The dbt project goes to your own Git.