AI that learns your business from your experts.
Then proves it.
ekai profiles your data in place, asks the people who hold the meaning, turns what they know into governed semantic models and production dbt pipelines, and verifies every definition against your warehouse before anything ships. Months of consulting, done in hours.
orders.status holds completed, returned, and settled_gw. Two I understand. What is settled_gw?
Legacy payment gateway. Real sales, count them in revenue. And revenue must match the finance close.
Anchored. customers.type shows 18% trial. Do trials count as active customers?
No. Active means a completed order in the last 90 days. Trials and returns are out.
dim_customers.sql · fct_orders.sql ✓
tests/ not_null · unique · relationships ✓
docs/ glossary · metrics · lineage ✓
How much of our revenue still comes through the legacy gateway?
Six percent last quarter, and shrinking. I resolved legacy gateway to settled_gw, per your expert, and it counts in revenue everywhere I report it.
And did active customers grow, excluding trials?
Yes, in every region. Trials and returns are already out, by definition.
The meaning of your data isn't stored with your data.
LLMs never learned your business
They were trained on the world's public data. Your KPIs, your definitions, your exceptions live in your experts' heads, not in your schema. No amount of prompting recovers knowledge that was never written down.
Manual extraction is slow
Semantic modeling engagements run months and six figures to document what your people already know. By the time the model is delivered, the business has moved and the model is already aging.
Unverified AI is a liability
Point a model at raw tables and it answers confidently and wrongly. Meaning that no one checked is meaning no one is accountable for, and one wrong number in a board pack costs more than the tooling that produced it.
The knowledge already exists. ekai gets it out of your experts, into your warehouse, and proves it before anyone relies on it.
Meaning first. Then structure. Then build.
Disciplined data modeling has always worked in this order. ekai automates it in this order, instead of mining query history and hoping the past predicts what the business needs next.
Draw on experts' knowledge
ekai profiles your data before it asks, so the exchange with your specialists is never a generic checklist. It arrives recognizing what it can and spends your experts' time only on what data cannot explain.
Model the data in place
From those profiles and your experts' input, ekai infers entities, keys, and relationships and drafts the logical model. Every inference is shown with its evidence. A human approves the model before it stands.
Generate, execute, verify
Production dbt code, tests, documentation, glossary, metrics, and lineage are generated together, executed inside your warehouse, and reconciled against the business facts your experts shared up front.
Structure follows meaning. Never the reverse.
Two workflows. One governed path from raw tables to trusted answers.
Discover
Connects read-only and learns your data where it sits, working with your experts along the way. The output is a reviewed entity model with inferred relationships and captured business context you can interrogate in chat.
Semantics
Turns the model into analytics the business signs off on: production code, tests, and documentation shipped as one governed unit, ready for questions and AI insights over exactly what shipped.
Net revenue: do returned orders reverse in the month of sale or the month of return?
Month of return. That's how finance books it.
Nothing ships unchecked.
Every platform can generate a model. ekai is built around the harder question: is it right? Generation is the easy half, so we made accountability the product.
- Anchored to business facts. Your experts state known truths up front. Every model must reproduce them before it can publish.
- Tests ship with the code. Schema tests, validation rules, and documentation are generated with every model, not bolted on after.
- Humans hold the gate. Inferred relationships, definitions, and metrics are reviewed by your people. ekai shows its evidence and takes correction.
- Neutral by design. ekai has no warehouse to lock you into and no incentive to model toward one vendor's stack. The output is standard dbt, YAML, and JSON you own.
Built to pass your security review, not to fight it.
Runs in your environment
Install as a Snowflake Native App inside your account, or as dedicated SaaS on AWS, Azure, or GCP. Fits your residency and procurement constraints, not ours.
Your data stays put
Read-only connections. Profiling happens in place, inside your warehouse. Nothing crosses the boundary: not rows, not profiles, not metadata.
Your LLM endpoints
Multi-LLM by design, including private routing through Vertex AI and Azure OpenAI, so model traffic follows your cloud agreements and compliance posture.
Warehouse-neutral
Snowflake, Databricks, BigQuery, Azure Synapse, PostgreSQL. One semantic approach across every platform you run today and whichever you run next.
Git-native by default
Every generated artifact is versioned to GitHub, GitLab, or Bitbucket. Your review process, your branch protection, your audit trail.
Open, portable artifacts
Standard dbt projects, YAML semantic views, JSON catalogs. Use ekai to build them; keep them forever.
One semantic approach, every warehouse you run.
| Platform | Data connection & ingestion | Artifact & model creation | Native semantic agent integration |
|---|---|---|---|
 Snowflake | |||
 Databricks | |||
 BigQuery | |||
 Postgres | |||
 Azure Synapse | — |
A native app, built for Snowflake from the ground up.
ekai runs as a Snowflake Native App: your data never leaves your account. Profiling, semantic modeling, and validation all execute inside your own warehouse, under your governance, with no separate infrastructure to manage.
Check out ekai for SnowflakeMeet the team making your data work for everyone.
Mo Aidrus
Co-founder & Chief Executive OfficerAs a x2 founder, and a long-time advocate for freeing trapped data value inside the enterprise, Mo spent 20+ years as Managing Director at Accenture & Rayn before setting out to build Ekai.
His goal was to fix three problems: the difficulty in accessing and exploring existing company data independently, not knowing the right numbers at the right time, and not being able to take full charge of data. Together with Hussnain, Ekai is meant to be the ultimate data companion for business users to quickly test data-driven ideas without relying on busy IT teams.
Hussnain Ahmed
Co-founder & Chief AI OfficerHussnain puts the AI in Ekai. He brings 20+ years of experience architecting innovative data strategy by introducing AI operations to tech teams.
At Ekai, he has been pivotal in developing and cementing the AI-first principles that position Ekai as a "Business Data Lab" for BAs or Analytic Engineers to build various data models without extensive IT involvement.
Tero Miikki
Chief Commercial Officer & Global Partnership LeadTero is a seasoned data leader and entrepreneur. As a CDO and data leader he has led major data/AI transformation and governance programs at UPM, a global manufacturing company, and advanced engineering practices at Microsoft.
Tero has also shaped data strategy at Sanoma Media Finland. With expertise in business development, go-to-market data cloud strategies, and IT procurement, Tero has served management teams, chaired governance boards, and overseen complex data ecosystems. In addition to his CCO role, Tero currently leads Ekai's global GTM efforts including its partnership with Snowflake.
Our core values.
Who we are and what we embody as a company.
Humility, Hustle & Heart
We know we're early so we will outwork the room and let the results do the talking.
Accountability
We own outcomes, not just effort. If it's broken, we fix it; if we said it, we do it.
Doing the right thing even when nobody is looking
Integrity isn't a policy, it's a habit.
Strong sense of urgency and a bias for action
Every week we don't move is a week a competitor does. We default to doing, not deliberating.
Relentlessly resourceful
We don't wait for a warm intro, a bigger budget, or a perfect moment—we find the path.
Curiosity & Creativity
We lead with curiosity & creativity and keep increasing our TQ.
Persistence & Patience
Every follow-up, every meeting, every proof point builds on the last. Consistent effort pays out.
See how data can be this easy in this short review.
Ekai Pricing.
This is a starter package to try out Ekai.
- 5 Semantic Models
- 75 Tables
Standard subscription for extensive semantic modelling
- 36 Semantic Models
- 350 Tables
Premium offering, unlimited semantic models
- Unlimited Semantic Models
- Custom Number of Tables
Ekai also offers add-on pricing, volume, and payment discounts. Contact our team to learn more.
See your own data modeled.
Bring one domain and three business questions. Leave with a reviewed model, the pipeline that builds it, and the tests that prove it.
