SimplyFleet Enables On-the-Fly Reporting with Text2SQL.ai
SimplyFleet embedded the Text2SQL.ai API to let customers ask questions in plain English and instantly generate SQL-backed reports. Result: faster insights, fewer support escalations, and a reporting UX users actually use.
Customer at a glance
Key details about SimplyFleet
- Name
- SimplyFleet
- Use case
- Self-serve reporting across multiple modules (maintenance, fuel, trips, etc.)
- Goal
- Unified, conversational reporting without building a heavy dashboarding layer
Challenge
SimplyFleet's reporting lived in separate modules (maintenance, fuel, trips). Users who needed combined views (e.g., "show all expenses last month across trips + maintenance + fill-ups") had to export multiple reports and stitch them together. Prior to their integration, many users were unhappy with the lack of access to essential data when they needed it, leading to customers finding an alternative. The team needed to solve this solution fast.
They considered a traditional drag-and-drop BI builder, but it felt complex for end-users and heavy to implement. They wanted a conversational, flexible experience that kept product control in-app without buying an expensive, bundled dashboard platform.
Why Text2SQL.ai
API-first
Fit their plan to build a chat-style reporting UI in their app (not a plug-and-play dashboard)
Time-to-value
Avoided building complex LLM infrastructure, including guardrails, schema handling, retries, error checks, etc. from scratch
Cost-effective
Alternatives (e.g., dashboard-centric tools) were far pricier
Responsive support
Quick answers from Text2SQL.ai team for support during integration
Solution
SimplyFleet added a Create Reports tab with prompt hints (e.g., "show my top 5 most expensive vehicles to maintain"). The UX guides users to describe the report, lets them adjust the result conversationally, and then save the final query.
This integration took less than one month for a single developer to build, thanks to the ease of implementation for the Text2SQL.ai API. It also worked out-of-the-box:
"Most requests generate the right SQL on the first try. When needed, our team can tweak the saved SQL and users are unblocked fast."
Results
- Adoption: Over 110+ organizations used AI reporting within the first month.
- Support: Only 4–5 report-assist tickets total; most queries worked out-of-the-box.
- Friction: Minimal—launch video + in-product prompts drove immediate use.
"We're seeing a lot of users adopt it quickly. The conversational prompts and saved reports make it feel like a native reporting module."
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