Playcall is the open-source alternative to Gong, built for AI-native GTM teams. Score every call against your playbook and the buyer context your rep was talking to. Works with MEDDPICC, BANT, SPIN, or upload your playbook and let AI generate the rubric. Get evidence-backed scores, missed moments, and outcome tracking. Every score comes with a coaching drill for the rep to run next. Self-hostable. No lock-in, no $30K/year contracts, or 10+ baked-in features your team never touches.
I've spent the last 5 years building GTM systems at AI companies like Sieve (YC W22), Ragie.ai, and Aviator (YC S21).
Most call intelligence tools are good at summarizing what happened, but weak at judging whether a rep actually followed the team's sales motion based on the buyer context/stage.
And context matters. A discovery call with a 50-person Series A startup buying a tool should not be scored the same way as a Fortune 500 vendor evaluation.
Here's the tell: the founders I know don't even trust Gong. They rawdog their team's calls themselves, rewatching every AE call, because $30K+/year of call intelligence still can't answer their actual question: did my rep say the right thing for this specific buyer?
So I built Playcall.
What Playcall does differently:
Buyer-Aware Scoring: Company stage, contact role, and deal context dynamically shape every scorecard.
Your Methodology, Not Ours: Score against MEDDPICC, BANT, SPIN, or your custom playbook. No framework? Upload your playbook and Playcall generates the rubric for you.
Outcome-Tied Scoring: Every score links to deal stage, outcome, and pipeline impact, so managers can see which behaviors actually move deals.
Coaching Drills, Not Just Feedback: Every score comes with a specific, actionable drill for the rep to run next.
Plug & Play with any LLM: Use your favorite model (Claude, GPT, Gemini, or 15+ others). No vendor lock-in.
Self-Hostable: Open source. Deploy to your own infrastructure. Data stays with you. You can run it for under $50/month, with LLM and enrichment usage as the main variable costs.
The goal is simple: help reps improve against the playbook they're expected to follow, help managers see which behaviors move deals, and spot objection patterns before they compound.
Would love feedback from founders, GTM leaders, RevOps folks, and sales managers.
Two questions I'd love answers to:
What's the biggest gap you've seen in existing call coaching/intelligence tools?
For automatic call ingestion, would you rather connect an existing notetaker like Granola, Fathom, or Fireflies or have Playcall ship its own Zoom/Meet/Teams bot?
re: your second question, I'd lean towards connecting to an existing notetaker (Fathom/Fireflies) rather than shipping your own bot. Reps already grumble about one bot joining, a second one showing up with a different name would just add confusion in the call and probably slow adoption. On the outcome-tied scoring though, I'm a bit skeptical for early-stage teams specifically - "which behaviors move deals" needs a real sample of closed-won/closed-lost to mean anything, and a 5-person startup team might only close a handful of deals a month. How many scored calls before that correlation stops being noise?
About Playcall on Product Hunt
“The open-source AI alternative to Gong”
Playcall launched on Product Hunt on August 26th, 2026 and earned 98 upvotes and 2 comments, placing #15 on the daily leaderboard. Playcall is the open-source alternative to Gong, built for AI-native GTM teams. Score every call against your playbook and the buyer context your rep was talking to. Works with MEDDPICC, BANT, SPIN, or upload your playbook and let AI generate the rubric. Get evidence-backed scores, missed moments, and outcome tracking. Every score comes with a coaching drill for the rep to run next. Self-hostable. No lock-in, no $30K/year contracts, or 10+ baked-in features your team never touches.
Playcall was featured in Sales (22k followers), Open Source (68.8k followers), Artificial Intelligence (477.3k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 170.9k products, making this a competitive space to launch in.
Who hunted Playcall?
Playcall was hunted by fmerian. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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fmerian
Hey Product Hunt 👋
I've spent the last 5 years building GTM systems at AI companies like Sieve (YC W22), Ragie.ai, and Aviator (YC S21).
Most call intelligence tools are good at summarizing what happened, but weak at judging whether a rep actually followed the team's sales motion based on the buyer context/stage.
And context matters. A discovery call with a 50-person Series A startup buying a tool should not be scored the same way as a Fortune 500 vendor evaluation.
Here's the tell: the founders I know don't even trust Gong. They rawdog their team's calls themselves, rewatching every AE call, because $30K+/year of call intelligence still can't answer their actual question: did my rep say the right thing for this specific buyer?
So I built Playcall.
What Playcall does differently:
Buyer-Aware Scoring: Company stage, contact role, and deal context dynamically shape every scorecard.
Your Methodology, Not Ours: Score against MEDDPICC, BANT, SPIN, or your custom playbook. No framework? Upload your playbook and Playcall generates the rubric for you.
Outcome-Tied Scoring: Every score links to deal stage, outcome, and pipeline impact, so managers can see which behaviors actually move deals.
Coaching Drills, Not Just Feedback: Every score comes with a specific, actionable drill for the rep to run next.
Plug & Play with any LLM: Use your favorite model (Claude, GPT, Gemini, or 15+ others). No vendor lock-in.
Self-Hostable: Open source. Deploy to your own infrastructure. Data stays with you. You can run it for under $50/month, with LLM and enrichment usage as the main variable costs.
The goal is simple: help reps improve against the playbook they're expected to follow, help managers see which behaviors move deals, and spot objection patterns before they compound.
Live demo: playcall.dphenomenal.com
Repo: github.com/Dphenomenal101/playcall
Would love feedback from founders, GTM leaders, RevOps folks, and sales managers.
Two questions I'd love answers to:
What's the biggest gap you've seen in existing call coaching/intelligence tools?
For automatic call ingestion, would you rather connect an existing notetaker like Granola, Fathom, or Fireflies or have Playcall ship its own Zoom/Meet/Teams bot?