At a glance
- AI agents
- Natural-language queries with code transparency (Python, SQL, R)
- Data
- 40+ connectors (BigQuery, Snowflake, GA4, Sheets, ...)
- Automation
- Data Flows, scheduled pipelines, embeddable dashboards
- Pricing
- Free · $20/mo Starter · $40/user Max · $80/user Business
Engagement
What it does
Better Analyst is an all-in-one analytics workspace. Connect 40+ data sources (BigQuery, Snowflake, GA4, Sheets, Postgres, ...), run natural-language queries via AI agents, and get back the SQL/Python/R the AI wrote alongside the answer. Build dashboards, schedule Data Flows, run text analysis, and embed the results elsewhere. Started as an English-to-Excel formula converter (FormulaBot); rebranded and expanded as the product grew.
What we built
Two senior engineers embedded with the founding team since 2023. Shipped the initial English-to-SQL LLM pipeline that replaced the rules-based v1 formula engine, then expanded into charts, dashboards, data pipelines, and the connector layer. Same Slack channels, same sprints, same codebase as the client team - no handoffs.
The technical work
The core challenge was an AI layer that could interpret natural language queries, generate correct SQL across multiple database dialects, and present results in a format non-technical users could use. We built the prompt engineering pipeline, the query validation layer, and the rendering engine for charts and tables. On the infrastructure side, we handled the migration from monolith to service-oriented architecture - splitting AI inference, data processing, and user-facing API into independently deployable services. That let the platform scale from thousands to 1.5M+ users.
Where it is today
Rebranded from FormulaBot to Better Analyst. 1.5M+ users, 40+ data connectors, AI agents, Data Flows, and embeddable dashboards in the current product surface. Two Zeroic engineers still embedded, now 3+ years into the partnership.
The people behind this project
Client
David Bressler Drove the product vision from a simple formula tool to a full chat-with-your-data platform. Defined the roadmap, prioritized features based on user feedback, and made the key calls on when to pivot the product direction.
Zeroic
Prashant Abbi Led the technical architecture and oversaw the migration from monolith to service-oriented architecture. Designed the AI inference pipeline and coordinated the engineering strategy across the full stack.
Shankar Prasad Built the core English-to-SQL engine and the prompt engineering pipeline. Owned the AI layer end-to-end - from query parsing to result rendering - and scaled it from thousands to over a million users.
Sudhanshu Sharma Shipped the frontend experience - charts, dashboards, and the data pipeline UI. Built the real-time rendering engine for query results and handled the user-facing product polish that made complex data feel simple.
and have been with FormulaBot for 3+ years. We started as a simple English-to-SQL formula generator. It's now a 'chat with your data' product serving 1.5M+ users. They built it like it was theirs.