Myriade vs Microsoft Fabric
Copilot requires you to build context manually.
Myriade builds it for you.
Myriade works with Fabric, not against it. It connects to Azure, Fabric, and OneLake as data sources and adds an AI intelligence layer on top, with zero vendor lock-in.
Data understanding
Skip the months of semantic modeling.
Myriade builds your context layer in days.
Fabric's AI capabilities have improved significantly. The OneLake Catalog now generates descriptions automatically, and Prep for AI lets you configure instructions and verified answers. But these features work one field at a time, one table at a time. Someone on your team still has to build the semantic model, define the relationships, add the synonyms, configure the instructions. For a warehouse with hundreds of tables, that is months of work.
Myriade does this warehouse-wide in days, by analyzing the data itself. It connects to your warehouse and reverse-engineers a context layer covering every table and column, with roughly 90% generated autonomously. The remaining 10% are genuine ambiguities that Myriade surfaces for your team to confirm, rather than guessing.
This is the difference between an AI that reads a description someone wrote for cstmr_lt and an AI that has examined the values, distributions, and relationships to know exactly what it contains.
Scope
Copilot answers questions about one report.
Myriade traverses your entire warehouse.
Fabric Copilot in Power BI works within the scope of one report or one semantic model at a time. The standalone Copilot can search across reports but is still bounded by existing semantic models. Data Agents can be connected to semantic models, but require configuration per model. If a table isn't modeled in a semantic model, Copilot cannot see or query it.
Myriade works warehouse-wide from day one. Every table is visible. Joins are inferred automatically and mapped within the context layer. If a business user asks a question that requires combining customer data with product data with logistics data, Myriade can traverse those tables without anyone having pre-defined the path.
Continuous learning
An AI that gets smarter every night, across every user, without you maintaining a thing.
Fabric Copilot caches responses for 24 hours on unchanged semantic models. Admins can pre-define verified answers and Prep for AI instructions per model. But there is no cross-session learning, no automatic improvement from user interactions. Myriade goes further in three ways.
Nightly memory cycle
Every conversation across your org is reviewed nightly. Corrections and clarifications become permanent knowledge for all users.
Org & user instructions
Define business rules that apply to everyone, or context specific to a team. The AI adapts without warehouse changes.
Self-improving context
The platform in month six is meaningfully more accurate than month one. Every interaction deepens the foundation.
Costs & incentives
Microsoft profits from your compute.
Myriade reduces it.
Fabric Copilot charges 400 CU-seconds per 1,000 input tokens and 1,200 CU-seconds per 1,000 output tokens. At pay-as-you-go rates, that works out to roughly $20/1M input tokens and $60/1M output tokens, compared to ~$2.50 and ~$10 for direct GPT-4o API access. That is a 7-8x markup on input tokens. Even with reserved capacity (~$0.107/CU-hour), the markup is still 4-5x. Every SQL query Copilot generates runs on your Fabric capacity, consuming additional CUs from the same pool as all your other workloads.
Myriade's AI pricing uses a fixed per-user fee with included token credits, at roughly 2 to 3x the direct API rate. And Myriade's FinOps Agent actively audits your warehouse spending, with customers consistently finding 27-40% in compute savings. Microsoft's revenue model is capacity-based: an AI layer that generates SQL is, by design, a compute consumption engine for its vendor. Myriade is structurally incentivized to reduce your infrastructure costs, not profit from them.
Markup vs. direct API pricing
Copilot + SQL queries compete for the same CU pool as all other Fabric workloads.
∞FinOps Agent actively reduces your warehouse compute.
-27-40%Multi-source & portability
Your intelligence should survive a cloud migration.
Fabric is Azure-native. Copilot, semantic models, Data Agents, and governance configs all live inside the Azure ecosystem. The raw data format is open (Delta Lake), and OneLake can shortcut to S3 and GCS. So the data itself is technically portable. But the intelligence layer (semantic models, Prep for AI configs, verified answers, Copilot context) does not transfer. If you migrate away from Azure, you rebuild from scratch.
Myriade connects to all major warehouses simultaneously. The intelligence layer (documentation, context, business rules) lives in Myriade and follows you across any supported source. If you migrate from Fabric to Snowflake, or add BigQuery alongside your existing setup, the context layer comes with you.
Currently supports up to 3 simultaneous connections.*
Feature comparison
Testimonials
Trusted by both data and business teams.
“We documented over 150 tables in less than a week with Myriade. 90% of the data was validated automatically.”
Jean-François Jouannais
Head of Data & AI Product
“I appreciate Myriade for its semantic ‘magic’, which understands our tables and handles complex joins.”
Solvita Jancevska
Data Steward
“Myriade helps me daily to optimize my queries, better understand business needs, and find information faster.”
Marius Saka
Lead Data Analytics @ Jules
“I was impressed pretty quickly because I don’t have a data background, and Myriade lets me do things I simply couldn’t do otherwise.”
Allan Lemoine
Head of Logistics @ Jules
“Myriade is the dream tool for anyone who wants to speed up decision-making. You analyze incredibly fast and dig deeper into results through conversation.”
Yohan Talik
Head of Performance @ Jules
“It’s like an automatic gearbox. Once you’ve tried it, you never want to go back.”
Fares Daoud
Tech Lead Data & AI @ Jules
“Myriade sees far ahead. In two months, we had an intelligence engine to analyze our data. It’s a magic wand for business teams.”
Moez Hamad
Chief Data Officer @ Jules
“Myriade helps me daily to optimize my queries, better understand business needs, and find information faster.”
Marius Saka
Lead Data Analytics @ Jules
“I was impressed pretty quickly because I don’t have a data background, and Myriade lets me do things I simply couldn’t do otherwise.”
Allan Lemoine
Head of Logistics @ Jules
“Myriade is the dream tool for anyone who wants to speed up decision-making. You analyze incredibly fast and dig deeper into results through conversation.”
Yohan Talik
Head of Performance @ Jules
“It’s like an automatic gearbox. Once you’ve tried it, you never want to go back.”
Fares Daoud
Tech Lead Data & AI @ Jules
“Myriade sees far ahead. In two months, we had an intelligence engine to analyze our data. It’s a magic wand for business teams.”
Moez Hamad
Chief Data Officer @ Jules
“Conclusive results and great internal adoption. Kudos for the product and what it delivers.”
Pierre-Antoine Roinat
CEO & Co-founder @ Recommerce
“With Myriade I can work 5 to 6 times faster than if I was trying to find things myself.”
Valentin Poulet
Head of Merchant Partnerships @ Ekip
“It’s ChatGPT for our data. Whenever I need information, instead of digging around, I ask Myriade and get my answer in 2 minutes.”
Angèle Miard
Customer Success Manager @ Ekip
“It’s like having a pocket data analyst. It runs incredibly precise analyses, spots bugs, and finds things that would have taken me hours to find on my own.”
Sandrine Eklou
Customer Success Manager @ Ekip
“Conclusive results and great internal adoption. Kudos for the product and what it delivers.”
Pierre-Antoine Roinat
CEO & Co-founder @ Recommerce
“With Myriade I can work 5 to 6 times faster than if I was trying to find things myself.”
Valentin Poulet
Head of Merchant Partnerships @ Ekip
“It’s ChatGPT for our data. Whenever I need information, instead of digging around, I ask Myriade and get my answer in 2 minutes.”
Angèle Miard
Customer Success Manager @ Ekip
“It’s like having a pocket data analyst. It runs incredibly precise analyses, spots bugs, and finds things that would have taken me hours to find on my own.”
Sandrine Eklou
Customer Success Manager @ Ekip
Frequently Asked Questions
AI on all your data, not just the tables someone had time to model.
Start with a risk-free warehouse audit that typically finds 27-40% in compute savings. Then see what happens when AI actually understands your data.
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