Building an AI-powered GTM Operating System: A F100 Success Story with PromptQL

A F100 global technology leader set out to reimagine its go-to-market (GTM) operations – and address one of the root causes of slowing revenue growth: fragmented, siloed customer data across dozens of systems.

With 50+ Salesforce instances and tens of thousands of sellers, marketers, and customer success reps, accessing the right insights – and acting on them - was slow, error-prone, and inefficient.

By partnering with Hasura and layering PromptQL into its GTM workflows, the company is building an AI-powered GTM operating system: one that not only unifies fragmented CRM data, but surfaces reliable, trusted insights to their GTM teams, leading to faster, smarter actions.

In the process, the company is not just improving forecast accuracy and accelerating revenue, it’s actually transforming how the company sells, serves, and grows.

Over several years of growth and acquisition, the company had accumulated 40+ Salesforce orgs across business units, geographies, and product lines. But this created a number of issues:

• Sellers couldn't see opportunities across divisions
• Customer success teams lacked a unified view of customer health
• Marketers struggled to personalize outreach based on the full customer context
• Leaders couldn’t get clean forecasts or understand deal risks across the enterprise

And critically, sellers themselves – the engine of revenue – felt the pain every day.

"Our CRM is the operating system of the business. If it’s fragmented, the whole system slows down."

To move faster, drive more pipeline, and deliver better customer experiences, GTM teams needed a way to unify all of the fragmented data without a massive replatforming platform. And in the process, they wanted to make it human-friendly but AI-driven.

That’s when one of the forward-looking technology leaders developed a vision: a solution that not just modernized or consolidated systems, but actually transformed how their globally distributed revenue teams work.

In their own words:

"We need to make the systems fun again. Easy again. It’s not just about capturing data; it’s about making it enjoyable and seamless for our teams to do their jobs."

Instead of spending hours wrangling fragmented CRM data, the vision was to create an operating system where every seller, marketer, and customer success rep could access trusted insights instantly – with just a question. A system where the AI acted as a co-pilot - not a barrier – to smarter execution. Global teams could collaborate without friction, even across dozens of systems. A system where revenue acceleration became intentional, not accidental.

That’s when they turned to Hasura.

To bring this vision to life, Hasura unified over 40 Salesforce instances, enrichment tools, and GTM systems into a single, queryable semantic graph – the GTM Supergraph.

This supergraph created a real-time, role-aware data layer where every customer-facing team – from sales to marketing to customer success – could access trusted data on accounts, opportunities, product usage, and campaign touchpoints through a consistent API.

PromptQL sits on top of the supergraph, transforming it into an AI-native interface where teams can ask complex, contextual questions like:

“Which high-usage opportunities have gone dark in the last 30 days?”

Instead of wrestling with dashboards or pinging RevOps, GTM users get conversational, real-time answers – grounded in trusted GTM data and tailored to their role. Now, GTM teams can finally access the unified, secure, and explainable insights they need to move faster and execute better.

Key Benefits

• Unified GTM Visibility: Sellers and success managers see opportunities, risks, and customer insights across all business units – in one trusted view – no matter where the data lives.
• Conversational Data Access: No more jumping between 50 systems, multiple tabs, reports and dashboards. Just ask a question in natural language - get structured, contextual answers.
• Role-Based Security: Granular access controls ensure users only see what they’re meant to, protecting sensitive customer and deal data.
• Multi-Step Reasoning & AI Workflows: PromptQL powers advanced use cases - from building account plans to diagnosing pipeline risk – with real GTM data, not hallucinations.

As one stakeholder put it:

"PromptQL makes the GTM supergraph conversational. Sellers don’t need to learn SQL or depends on revenue analysts. They just ask questions and get real answers."

Today, the AI-powered GTM operating system isn’t just on a vision-board. It’s real, it’s in production, and it’s already unlocked a number of “use cases” that were just not possible before:

• Account Plan Generator: Sellers can generate rich account plans with SWOT analyses, growth strategies, and relationship maps – all in minutes, not days.
• Opportunity Risk Analyzer: Sales teams can identify stalled or slipping deals based on real engagement and activity trends across orgs.
• Upsell Signal Detector: Customer success managers can surface expansion-ready accounts based on milestones, usage trends, and product adoption signals.
• Cross-Org Opportunity Views: Revenue leaders can finally see a "one company" view of customer pipeline, driving better forecasting and GTM coordination.

And because PromptQL automatically explains the logic behind every insight, users trust what they see – a crucial breakthrough for adoption.

For enterprises in general – and for sellers in particular – trust is everything. If AI insights are wrong – or even just questionable – sellers will disengage, customers will feel the impact, and revenue will suffer.

That’s why reliability was a non-negotiable:

"If the AI’s insight isn’t better than a seller’s napkin math, we lose trust - and the tool dies."

For this technology giant, PromptQL is fundamentally changing how GTM teams interact with data – by addressing the key reliability and trust challenges that typically plague AI systems.

Here’s how PromptQL does it.

1. First, PromptQL decouples planning from execution, building structured, verifiable query plans before touching live data – grounding every AI response in reality, not guesses.
2. Then, it enforces strict field-level, role-based access, ensuring users only see the data they’re authorized to view, even across complex cross-system queries.
3. On top of that, it chains together multi-step, explainable reasoning, showing users exactly how insights were generated.
4. Finally, it’s built to self-correct - intelligently prompting, retrying, or flagging issues when data is missing or unclear - keeping users in control without slowing them down.

The result? AI that’s not just faster – but reliable enough for critical GTM workflows.

"AI isn't replacing our sellers – it's making them smarter, faster, and more connected."

Building on these successes, the company sees opportunities in additional GTM areas such as:

• Pre-built AI workflows: Save and reuse successful PromptQL programs (e.g., “Prepare QBR deck for account X”) with one click
• Proactive AI insights: Deliver “weather reports” on account health, growth risks, and cross-sell opportunities before meetings
• Extensible agent ecosystem: Allow internal AI agents (like sustainability data, risk monitoring) to plug into the GTM Supergraph

And at every step, the company remains committed to keeping humans at the center – because the goal isn’t just a smarter GTM system, it’s a smarter, faster, and more human GTM motion.