Connect your Zendesk, Gong, and Salesforce — and know exactly which customer problems are costing you the most revenue. That’s PDSA.
Product Discovery Synthesis Agent — built for enterprise product teams.
"The SSO integration with Okta keeps failing. Our enterprise security policy requires SSO and we can't onboard our team without it. This is a hard blocker."
A real Series C company prioritized "performance issues" based on 2,000 support ticket mentions. When feedback was weighted by ARR, performance issues represented only $200K of revenue impact.
Meanwhile, "missing SSO" appeared just 34 times — but represented $2.4M in at-risk ARR.
“PDSA surfaced a $2.4M SSO blocker we had been deprioritizing for a quarter. We shipped it in the next sprint. That single insight paid for the tool a hundred times over.”
SKSarah KimVP of Product, Series C SaaS · $45M ARR
Decomposes long-form text into discrete, atomic claims of ≤2 sentences each. Every claim traceable to the source.
Embeds each claim using vector embeddings. Compares against existing themes. Routes to HITL at 70–84% confidence.
Cross-references CRM to attach ARR. Calculates Weighted Severity = Σ(ARR × Frequency) / Total Active ARR.
Connect Zendesk, Gong, Salesforce, App Store, and Slack. All feedback normalized into a unified schema automatically.
Extraction, Clustering, and Quantification agents work in sequence. Each with a single responsibility, independently evaluated.
Every insight is weighted by customer ARR. A $500K customer's complaint carries more weight than a free-tier user's.
Low-confidence clusters route to your review queue. Approve, Merge, or Reject — every action improves future accuracy.
Real-time spike detection. When a theme's mentions jump 200%+ in 24 hours, you know before your customers escalate.
Track Clustering Accuracy, Hallucination Rate, HITL Override Rate, and Time-to-Insight. Drift detection built in.
All three PDSA agents are open-source. Run them as Python scripts, or copy the prompts directly into ChatGPT or Claude — no setup required.
# Install and run in 3 commands pip install -r requirements.txt cp .env.example .env # add your OpenAI key python run_pipeline.py --input data/sample_feedback.json --output results/
PDSA has a formal Behavior Specification — constraints, failure modes, and fallback behaviors. Every insight must cite ≥3 source quotes. Zero-evidence claims are auto-rejected.
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