How a 200-Person SaaS Transformed Ad-Hoc Data Requests into a $50K/Year AI Analyst Upsell
"This embedded AI Analyst instantly became a sellable add-on that not only unlocked new revenue but also kept pace with the fast-changing demands of our customer base—a game-changer for our roadmap."
CEO @ B2B SaaS Company
Summary
A B2B company embedded an AI Analyst agent—powered by Inventive—into their SaaS product, reading directly from their existing governed Looker models. They started testing an initial version within hours, released self-serve AI analytics in an alpha pilot to early customers in under three weeks, and rolled out a production-ready beta in under three months as a new $50K/year SKU.
Key Metrics
Accuracy: >96% factual precision in production evaluations
Latency: p50 = ~30 seconds, p95 = ~45 seconds
Revenue: $2M+ in Annual Recurring Revenue (ARR) pipeline generated in first 90 days
The Problem
Rising cost to serve. The company was spending >$500K/year on Customer Success Managers (CSMs) answering ad-hoc analytics requests and coordinating between customers and the data team, rather than investing time in more strategic relationship building and account development.
Competitive pressure. They lost head-to-head deals to a faster-moving competitor with better AI-powered self-serve analytics capabilities.
Stalled revenue opportunity. Their customers signaled they would eagerly pay tens of thousands per year for fast, high-quality self-serve AI analytics, but both their in-house build and their BI tool's internal-focused AI couldn't meet the quality bar that external customers demand, wasting valuable engineering effort that should have been spent on core competencies.
The Solution
They embedded Inventive's AI Analyst—white-labeled as their own custom-branded AI—as a premium self-serve add-on that transformed how customers interacted with their data. Purpose-built for external customer-facing embeds, it complemented their existing BI investment by handling the long tail of ad-hoc analytics that BI dashboards and in-house builds couldn't reliably solve. Instead of waiting on CSMs for ad-hoc requests, customers now self-serve using natural language and receive fast, accurate analyses grounded in verifiable queries on governed data.
To stay competitive as customer expectations evolved, the AI flexed to changing needs, personalizing responses based on usage patterns, allowing customers to merge custom external data sources (social media, internal knowledge base) for richer analysis, and suggesting relevant in-product custom actions.
And because of Inventive’s white-glove implementation partnership, the engineering team avoided months of AI development risk and stayed focused on core competencies—going from kickoff to production beta in under three months.
Why Inventive Works: Three Breakthroughs
Implementation Timeline
Kickoff (25–45 minutes): Inventive connected to the company's Looker instance live on the call, whitelisted initial customer-facing data models, autogenerated initial AI context, flagged gaps for the data team, and delivered a testable custom AI Analyst within hours—no months-long integration project required.
Alpha Pilot (<3 weeks, deployed from 1% to 10% of customers): The team launched the alpha build to early customers, evolved the initial AI context from real usage across diverse customers, all while monitoring for quality to avoid regression using a tailored set of automated evals.
Production Beta (<3 months): The team expanded AI Analyst scope and data coverage, scaled up testing and evaluation, then confidently launched a beta to the full customer base. The continuous learning feedback loop meant quality improved throughout customer rollout. Meanwhile, the internal product team gained new visibility into what customers wanted to do with their data and identified new strategic capabilities for the product roadmap.
“Our in-house build and BI tool's AI couldn't hit the quality bar for a premium customer-facing product. Inventive's continuous learning system closed the gap and keeps quality high—enabling our $50K/year upsell.“
CEO
B2B SaaS Company
Impact
Generated $2M+ in ARR pipeline in the first 90 days
Saved >$500K/year in CSM time previously spent on ad-hoc analytics
Unlocked new capabilities and customer demand insights that informed the product roadmap
About Inventive
Inventive helps B2B SaaS companies embed customer-facing AI Analysts that handle the long tail of ad-hoc analytics requests with a premium self-serve experience. Unlike AI tools built for internal use, Inventive is purpose-built for external embeds—giving product teams the tooling, visibility, and confidence to manage AI as a real product.
What makes us different:
White-glove partnership: We co-create your custom AI Analyst alongside your team, not just hand you a platform
Built for external embeds: Product management tooling designed for customer-facing AI—track performance, test changes, version with git, ship improvements
Industry-leading feedback loop: Continuous learning captures what works from every interaction, making your custom AI Analyst measurably smarter over time
Founded in 2022 and based in San Francisco, our team brings decades of domain expertise building data products and platforms at Google, Microsoft, and Meta. Our customers focus on their core competencies while we extend their data capabilities to reach the long tail of their customers' analytics needs.
If you’re a product or company leader curious to learn more, schedule time with us. Or follow us on LinkedIn and X/Twitter.
