Plugging an LLM into your database is not a data strategy.

Homegrown Text-to-SQL hallucinate because they skip the hard part: understanding your data. ThoughtSpot requires endless manual modeling. Myriade builds the data foundation automatically.

The mirage of AI 'connected to data'

Under pressure to integrate AI, your team tried connecting an LLM directly to the database. It felt like magic, until the hallucinations started. Wrong table joins, misunderstood metrics, inconsistent numbers. The fundamental issue isn't the AI model. It's that enterprise data is poorly structured, undocumented, and riddled with ambiguity.

Hallucinations: the LLM doesn't understand your data model and generates incorrect SQL. Numbers are wrong, and nobody detects it until a VP shows up at a board meeting with the wrong revenue figure.

No data foundation: Text-to-SQL tools skip documentation and governance. They hope raw data is clean enough. It never is.

ThoughtSpot's modeling burden: reliable answers require massive upfront manual modeling for each data source. Few companies have the bandwidth.

Costly internal builds: the 'build in-house' project ties up 2-3 engineers for 6+ months, with ongoing maintenance and a fragile result.

Myriade vs ThoughtSpot / Build in-house (Text-to-SQL)

Feature

Myriade

ThoughtSpot / Build in-house (Text-to-SQL)

Data understanding

AI auto-documents your data before querying it: statistical profiling, sampling, cross-table analysis

No data understanding, raw LLM on raw data

Answer reliability

~80% accuracy on messy data. Shows reasoning, pauses when uncertain.

Frequent hallucinations (raw Text-to-SQL)

Modeling effort

90% auto-generated documentation in 72h

ThoughtSpot: months of manual modeling / In-house: none

Transparency

Editable SQL, visible reasoning, human-in-the-loop

Black box, hard to verify answers

Time to value

72h deployment, value in the first week

ThoughtSpot: months / In-house: 6+ months

Multi-source

Query across Snowflake, BigQuery, Databricks, Redshift simultaneously

Limited to one source or complex integration

Why VP Data choose Myriade

Why teams choose Myriade

Reliability through data understanding, not brute force

Myriade doesn't just generate SQL. It first understands your data through statistical profiling, sampling, and cross-table analysis. When it encounters ambiguity, it pauses and asks instead of guessing. That's the critical difference versus tools that skip the foundation.

90% of documentation handled automatically

Instead of spending months fixing data models manually, Myriade's AI agent reverse-engineers your warehouse and proposes descriptions for every table and column. Your team validates instead of writes.

Security your CISO will approve

Read-only access. AI queries but never modifies your data. Self-hosted option available. Zero data retention, zero training on customer data. GDPR compliant.

Frequently Asked Questions

An LLM alone doesn't know your data model, naming conventions, or business rules. It generates syntactically correct but semantically wrong SQL. Myriade solves this by understanding your data first, through autonomous documentation and quality analysis.

Stop guessing. Start understanding your data.

See how Myriade builds the data foundation that makes AI analytics reliable, in 72h, not 6 months.