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How TrueFoundry Turned Discovery Calls into Data-Driven Conversations

How TrueFoundry Turned Discovery Calls into Data-Driven Conversations

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About True Foundry

TrueFoundry builds in the AI/ML infrastructure space with two core offerings:

  • Deployment Platform for ML & GenAI workloads (training, fine-tuning, GPU orchestration, production deployments).
  • LLM + MCP Gateway that adds governance, budget/rate limits, data residency, sensitive-data guardrails, and usage visibility across enterprise AI.

ICPs & buying roles

  • Gateway: VP/Head of Platform Engineering, Chief AI Officer, Chief Digital Officer, VP of Generative AI Engineering.
  • Deployment Platform: CTOs, Engineering VPs, Heads of Data Science, ML/Data Science teams.

GTM stack

CRM: Salesforce (recently migrated), HubSpot (for ebooks and legacy forms)

Outbound: Lemlist (LinkedIn + email + calls)

Analytics: PostHog, Google Search Console, Google Analytics, Ahrefs

Intent Signals: Reo.dev

GTM Motion Before Reo.Dev

Before adopting Reo.dev, TrueFoundry relied on outbound, events, and hiring signals using tools like Sambal and Factors AI. The team wanted a consolidated view of what prospects were actually exploring. They needed to walk into every conversation with context: buyer interests, terminology (AI gateway vs. LLM gateway vs. MCP gateway), and competitive engagement.

With Reo.Dev

Instead of starting from a blank page, TrueFoundry’s GTM motion now begins and runs on verified buyer behavior:

1) Pre-discovery, arrive prepared

  • Identify which pages a lead or company viewed (e.g., MCP Gateway vs. LLM Gateway).
  • Mirror the buyer’s own terminology to reduce friction in the first five minutes.
  • Spot early signs of competitive interest (e.g., starred repos).

2) During POV, personalize with live signal

  • Track accounts through the POV window to see what they’re doubling down on.
  • Watch GitHub activity around open-source competitors (stars, issues) to tune narrative and feature emphasis.
  • Prioritize the features and guardrails the buyer is already exploring.

3) Qualify faster with precise segmentation

  • Use advanced filters (revenue, employee size, nonprofit exclusion, web behavior) to tighten focus.
  • Keep the POV/post-discovery effort centered on accounts with real traction.
“We have more than 950 pages. Knowing exactly where a prospect is spending time tells us their focus - and the language they use. That prep shows up in the call.” - Konpal, Director @TrueFoundry

The Impact

  • Discovery calls feel targeted, not generic. The team arrives with a shared understanding of the buyer’s interests and vocabulary.
  • POVs are more relevant. Live insight into what prospects are evaluating (and which repos they watch) sharpens the POV plan.
  • Cleaner internal alignment. Sales and product speak from the same intent signals throughout evaluation.

Favorite Reo.Dev capabilities

  • Advanced Segments: layered filters across firmographics and behavior to zero in on qualified activity.
  • Competitor context via GitHub: real signals around open-source alternatives during evaluation.
  • Account behavior tracking: a running feed of what buyers actually read and revisit.
  • Support: “Nikita and Pratyush are really good to work with… it sets the bar for how we want to support our customers too.”
I would recommend Reo.dev to other devtool companies. I’ve already recommended it to friends.” - Konpal, Director @TrueFoundry
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