AI-Powered Product Intelligence

From Raw Signals to Shipped Product. Instantly.

ProductMind turns customer interviews, support tickets, NPS feedback, and call notes into structured PRDs and ticket breakdowns — with complete AI memory and traceability.

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% Reduction in PRD draft time
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Artifact types generated automatically
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% Evidence-grounded output
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Minutes from upload to approved PRD
End-to-End Workflow

Seven steps. One intelligent loop.

Watch how ProductMind transforms raw product signals into shipped output — fully automated, fully traceable.

1
Ingest Sources
Upload files & transcripts
2
Extract Themes
AI synthesis + clustering
3
Problem Statement
Structured framing
4
Generate PRD
Full spec with ACs
5
PM Review
Edit, feedback, approve
6
Ticket Breakdown
Engineering-ready tasks
7
AI Learns
Memory & preference loop
Theme Analysis
Problem Statement
PRD
Tickets
Activation Drop Onboarding Confusion Empty State UX Permission Model Role-based Paths CSV Import Friction
Synthesised from 5 sources · 38 unique signal fragments · Evidence-grounded
PROBLEM STATEMENT
New users experience low activation (avg 46%) in their first 7 days, primarily due to an empty initial state, unclear permission model, and no role-differentiated onboarding path — resulting in elevated support load and poor week-1 retention across SMB and mid-market segments.
Backed by 12 support tickets + 3 customer interviews
Objective
Increase 7-day activation rate from 46% to 70% by shipping a guided onboarding experience with role-based paths and quick-win milestones.
Requirements (P0)
Setup checklist · Role selector · Guided first action · Empty state content · Progress persistence
Success Metrics
Day-1 activation ≥ 60% · Time to first action < 20 min · Support tickets in week 1 reduced by 50%
P0 Implement Role Selector in Setup Wizard
P0 Add Onboarding Progress Checklist Component
P1 Design Empty State with Guided CTAs
P1 Role-based Welcome Email Trigger
+ 8 more tickets · All inside ProductMind · No Jira required in V1
Features

Built for product teams
who move fast.

Voice + Text Commands
Speak or type naturally. Say "Generate a PRD for onboarding redesign" and ProductMind handles the rest.
▸ COMMAND
AI Memory & Preference Learning
ProductMind remembers your editorial style, preferred PRD structure, and team vocabulary. Every revision teaches it to write more like you.
Prefers JTBD framing ACs in Given/When/Then 3-tier priority model Metric-first objectives Mobile-first scope Concise section headers
Live Trace & Explainability
Watch the AI's reasoning unfold in real time. Every decision is traceable to source evidence.
▸ Classifying intent…
▸ Loading 5 source docs into context
▸ Running theme extraction model
▸ 6 themes identified · confidence 0.91
▸ Drafting problem statement…
▸ Artifact saved · ID: art_prd_008
Activation Trend
Ground every feature decision in real usage data. Activation metrics drive priority, not gut feel.
Activation rate • last 10 weeks
Revision History & Restore
Every version is saved. Compare diffs, restore a prior draft, or see exactly what the AI changed and why.
v3
Regenerated with mobile focus
2 min ago
v2
Manual edit — ACs updated
14 min ago
v1
Initial generation
31 min ago
Runs 100% Locally
Your IP never leaves your machine. ProductMind runs on local Ollama models with zero cloud dependency. Enterprise-ready privacy by default.
One-Click Setup
Start the full stack with a single launcher\start.bat. Models pull automatically. Browser opens when ready.
How It Works

Every step, explained.

A transparent look at what happens between upload and shipped ticket.

01
Upload Your Raw Signals
Drag in any combination of customer interview notes, support ticket exports, NPS text, sales call transcripts, and usage CSVs. ProductMind accepts .txt, .csv, .pdf, and .md. Invalid types are rejected at the boundary.
TXTCSVPDFMarkdownType validation
01_customer_interviews_onboarding.txt
02_support_tickets_onboarding.csv
03_nps_feedback_onboarding.txt
04_sales_call_notes_onboarding.txt
05_usage_metrics_onboarding.csv
✓ 5 sources ingested · 247 chunks indexed
02
AI Extracts and Clusters Themes
The model reads all sources simultaneously, identifies recurring pain signals, and clusters them into labelled themes. Every theme is linked back to specific source fragments so you can audit the evidence.
RAG retrievalSemantic clusteringEvidence links
Activation drop
Onboarding UX
Empty state
Permission model
Role-based paths
Import friction
03
Generate Problem Statement & PRD
With a single command, ProductMind produces a structured Problem Statement and a full PRD — complete with objectives, scope, prioritised requirements, acceptance criteria in testable format, and measurable success metrics.
Structured outputAcceptance criteriaMetric-first
Problem
46% activation rate in week 1, driven by empty state and unclear setup flow.
Objective
Reach 70% day-7 activation with role-based guided onboarding and milestone tracking.
P0 Requirements
Setup checklist · Role selector · Progress persistence · Empty state CTAs
Success Metrics
Day-1 activation ≥ 60% · Time to first action < 20 min · Support tickets ↓ 50%
04
PM Reviews, Edits, and Approves
You own every artifact. Edit inline, give targeted feedback ("focus more on mobile"), and hit Regenerate. ProductMind learns from each revision. Approve the PRD and it auto-chains into ticket generation.
Inline editingFeedback regenerationApproval gateMemory learning
PM Feedback
"Focus more on mobile onboarding and include success metrics per role."
✓ PRD Approved — v3
Chaining into ticket breakdown…
Early Access Feedback

PMs who've tried it, love it.

★★★★★
"I uploaded call notes at 9am and had a stakeholder-ready PRD by 9:17. That used to take a full day. ProductMind is the first AI tool that actually follows my editorial style."
SR
Sarah R.
VP Product · Series B SaaS
★★★★★
"The evidence linking is a game-changer. When an exec challenges a requirement, I can point directly to the 7 customer interviews that back it. Zero hallucination in my test runs."
MK
Marcus K.
Head of Product · Fintech Scale-up
★★★★★
"Runs entirely on my laptop. My legal team was thrilled — no data leaves the machine. The memory feature means it gets better every sprint, not worse."
PL
Priya L.
Product Director · Enterprise
Seed Round Open

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