Ralph Gootee, CTO and Co-Founder at TigerEye, leads the development of a business simulation platform designed to enhance strategic decision-making, planning, and execution. By leveraging advanced time-aware AI technology, TigerEye enables organizations to streamline planning processes, simulate various scenarios, and make data-driven decisions more efficiently.
Founded by Gootee and former PlanGrid executives, TigerEye addresses common challenges in business planning, such as outdated spreadsheets and prolonged planning cycles, with a focus on adaptability and predictable growth. The platform integrates principles from industries like construction and software QA to provide dynamic solutions that help businesses optimize operations and scale effectively.
What inspired you to start TigerEye, and how did your previous experiences with PlanGrid influence your vision for the company?
I’ve always found data to be a challenge. Back when we built my last company, PlanGrid, tools like Looker and Redshift were just coming out. The concept of insights was new. Mixpanel and Amplitude were still in their early days. These products were so fresh that you had to build your own data engineering team to handle any kind of data insights.
At PlanGrid, we assembled an incredible team with PhDs and talented leaders who did impressive work: identifying hot leads, analyzing customer connections, and calculating ARR. But it took a 10-person team, was expensive, and left analysts feeling like ticket crunchers, running SQL queries to answer segmentation and growth questions. When they eventually moved on to lead data science teams elsewhere, the remaining team was often left struggling to make sense of the dashboards they left behind, leading to significant wasted time. Additionally, our CFO manually verified those numbers to ensure accuracy.
As a board member at other companies, I saw the same pattern: disconnected dashboards that were hard to piece together into actionable insights. During the Autodesk acquisition of PlanGrid, these challenges became even clearer. Managing two Salesforce environments and coordinating basic back-office tasks like CRM, ERP, and marketing was a struggle. Even determining which campaigns were working was a mystery. These frustrations inspired the vision for TigerEye: a way to make data seamless, actionable, quick and accessible.
TigerEye offers a flexible AI solution for go-to-market teams. What challenges in the market did you identify that led you to design a conversational AI for business intelligence?
Go-to-market analytics often feel overwhelming as it is packed with numbers, stats, and heavy math. The process of asking creative, investigative questions is clunky. You might create a ticket for the data team, asking for something like a win rate graph. There’s back-and-forth clarification, delays, and sometimes you realize you asked the wrong question. For most people, it’s neither an enjoyable nor a fast process especially for those without the authority of a C-Suite executive to fast-track responses.
Conversational AI changes that. Imagine just saying, “Show me win rates for the West Coast in pink versus the East Coast in brown, over the past four quarters, in a bar chart.” A conversation like that takes seconds and so does the output. We designed TigerEye to give users an intuitive “junior analyst” they can talk to — always available to create insights without the need for a clunky interface.
What were the most significant hurdles you faced during the early stages of TigerEye’s development, and how did you overcome them?
One major surprise was the sheer scale of data we encountered, regardless of company size. Even mid-market companies often have vast amounts of data that change frequently. Existing tools like Looker couldn’t handle these workloads efficiently; we saw load times of 10–12 seconds for a single graph. That’s unacceptable for today’s fast-paced business environment.
To address this, we had to innovate. We integrated DuckDB for faster query execution and chose Flutter for building a lightweight, efficient interface. Additionally, we contributed back to the open-source community by developing and maintaining DuckDB.Dart, enabling seamless integration with Dart and Flutter environments. These technologies allowed us to optimize for speed, flexibility and scalability.
As a co-founder, how did you and your team prioritize features and capabilities for TigerEye’s launch?
We started by putting the entire company’s resources behind the AI Analyst vision. This meant every front-end and back-end engineer contributed. The nature of an AI analyst required a full-company effort because it’s not just about text output; it’s about providing interactive widgets, configuring simulators, and enabling analysts to take meaningful action. For example, one feature lets users configure a future plan to add 10 reps to the West Coast seamlessly, which involves designing a highly interactive and intuitive system.
The development process had its ups and downs, but the technical backbone was built on rigorous evaluation. This became the core of our prioritization. Evaluation is where the real work happens. We’re constantly asking, “Did this change make the system better or worse?” We started with our engineering team and our domain experts and eventually evolved to capturing customer questions to refine our system further.
We introduced an automated test suite where the AI evaluates itself and assigns a score to determine if changes are improvements. To ensure accuracy, we still conduct human evaluations weekly to prevent biases like an LLM giving itself top marks. This dual-layer approach has been crucial to getting TigerEye to a “1.0” state and continually raising the bar.
Finally, achieving domain-specific alignment was a major focus. Sales and go-to-market operations demand precise, specialized answers, and alignment across stakeholders isn’t always straightforward. This is why domain expertise and real-world customer feedback were critical in shaping TigerEye into the platform it is today.
How does TigerEye’s approach differ from traditional BI tools, and what impact has this had on adoption rates among businesses?
TigerEye was built from the ground up with AI and mobile, offering a solution that is inherently portable and designed to answer questions quickly. Unlike traditional BI tools, which are slow and often require extensive configuration, TigerEye prioritizes speed and ease of use through conversational AI.
Our graphs and widgets are highly flexible, with interactive visuals that allow users to explore data intuitively. The AI doesn’t rely on generic, surface-level information that can lead to inaccurate responses; instead, it’s specialized to deliver precise, structured metrics tailored to each business.
Whether for startups, midmarket, or enterprise companies, TigerEye ensures consistency by grounding all calculations in SQL, enabling both front-end and AI-driven queries to deliver the same reliable numbers. We also provide transparency by showing customers the math behind our analysis, ensuring they understand exactly how the TigerEye platform arrived at its responses. This commitment to clarity helps build trust and confidence in the insights delivered.
The result is an AI platform that delivers strong customizability while empowering teams to access actionable insights independently, allowing data teams to focus on more strategic tasks. This approach has accelerated adoption among businesses looking for intuitive, scalable, and precise tools to enhance their decision-making.
How does TigerEye leverage AI to adapt and learn from CRM, ERP, and marketing automation changes in real time?
TigerEye uses AI, including Retrieval-Augmented Generation (RAG) and integrations with real-time APIs, to adapt dynamically to changes in CRM, ERP, and marketing automation platforms. We also combine GenAI with more traditional machine learning and simulation theory to give our AI the ability to predict the future. By connecting directly to these systems, our company continuously monitors updates, such as new customer records, changes in deal stages, or campaign performance metrics, ensuring insights remain current and actionable.
Our AI Analyst doesn’t just passively report data; it learns and evolves with customer workflows. For example, if a sales team modifies its pipeline structure, TigerEye quickly identifies the changes and adjusts its calculations, forecasts, and recommendations accordingly. This real-time adaptability eliminates manual updates and ensures leadership and teams always have an accurate, up-to-date view of their go-to-market performance.
Also, TigerEye’s flexibility allows it to work across multiple systems, ensuring seamless integration and alignment. Whether it’s Salesforce, HubSpot, NetSuite, or other platforms, TigerEye’s AI enables teams to cut through complexity, delivering timely, reliable insights that drive smarter, faster decision-making.
With increasing complexity in go-to-market operations, how does TigerEye simplify decision-making for leadership and teams?
Actionable insights through conversational AI. Traditional BI tools often require teams to navigate cumbersome dashboards, wait for data teams to generate reports, or manually piece together metrics across siloed systems. TigerEye eliminates these bottlenecks by providing instant, AI-driven answers tailored to leadership and teams’ needs.
Our AI Analyst functions like a proactive, junior team member, capable of responding to questions such as, “What’s my win rate in Q4 across regions?” or “How would adding five reps to the East Coast impact ARR?” The platform delivers insights in seconds without the need for data modeling or extensive setup.
By integrating AI with tailored business intelligence, TigerEye ensures that all metrics are accurate, consistent, and aligned across the organization. Leadership gains clarity on strategic decisions, while teams benefit from tools that surface trends, predict outcomes, and reduce the noise of operational complexity. TigerEye helps business leaders make faster, smarter decisions without the heavy lift.
How do you see conversational AI transforming business intelligence over the next five years?
Business intelligence is currently at a crossroads. Many tools remain stuck in an older or acquired state. They’re slow to innovate, lacking new products, and overly generalist in their approach. These legacy solutions weren’t built from the ground up to integrate with large language models or to offer AI interoperability. In most cases, they’re trying to retrofit outdated systems with unproven AI solutions, which isn’t moving the needle.
Conversational AI will drive a new breed of specialized BI applications. These tools won’t require teams to spend countless hours customizing and building solutions — they’ll be tailored from the outset to address specific needs in finance, sales, marketing, construction, oil and gas, and other industries. Each market is evolving differently, and specialization is key.
Foundational AI models like OpenAI, Anthropic, and Mistral will continue to handle broad, generic applications, but the future of BI lies in specialized vertical solutions that address unique problems. Specialized AI tools for BI will replace the current one-size-fits-all approach, enabling businesses to extract insights faster and more accurately. It can deliver precision and actionable insights within its domain. This shift will redefine BI as we know it.
After serving as a visiting partner at Y Combinator, how has mentoring startups influenced your leadership style or approach to innovation?
YC taught me the importance of prioritizing people. I learned to focus my energy on founders who were hungry, open to feedback, and relentlessly tenacious. Those traits — grit and adaptability — are hallmarks of successful teams, and I’ve carried that into TigerEye.
Another lesson was recognizing the value of diversity, both in thought and background. At YC, I saw firsthand how founders from underrepresented groups often brought incredible resilience and creativity to the table. It’s a perspective that’s shaped how we build and lead at TigerEye today. Diversity strengthens teams and drives innovation.
What’s your vision for the future of TigerEye, and how do you plan to expand its impact across industries?
TigerEye is first and foremost an AI company. Our goal is to bring the innovations we see in consumer AI, like the seamless interaction in tools like Perplexity and Cursor, into the enterprise. Imagine a personal assistant that you can ask for insights anywhere, on any device. Need to know why deals stalled in Q2 or what would be required for you to double your sales headcount in a certain region while you’re on the move? You ask, and it’s there instantly, accurate and consistent across the company.
The future of TigerEye is about simplifying access to data and making insights ubiquitous, whether you’re using a mobile app, wearing a smartwatch, or asking for a report in Slack. We’re focused on creating tools that make data-driven decision-making effortless.
Thank you for the great interview, readers who wish to learn more should visit TigerEye.
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