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Obsidius

Customer feedback, turned into something your team can actually build.

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How Obsidius works

Six steps from raw customer feedback to implementation-ready specs. Powered by a multi-model AI engine that uses the best model for each task.

1
Step 1

Ingest

Paste feedback or upload a CSV. Every feedback item is preserved with its source and timestamp. Integrations with Jira, Slack, GitHub, and more.

2
Step 2

Classify

AI reads each piece of feedback and extracts the type (feature request, bug, churn signal), sentiment, urgency level, and product area — in seconds.

3
Step 3

Group

Related feedback is automatically grouped into patterns. Instead of 200 individual tickets, you see 8 clear priorities with supporting evidence.

4
Step 4

Score

Each pattern is ranked by a weighted formula: 40% frequency, 35% recency, 25% urgency. The things that matter most rise to the top.

5
Step 5

Generate

For each priority, Obsidius writes a full implementation spec: problem statement, user stories with real personas, testable acceptance criteria, technical approach, and effort estimate.

6
Step 6

Act

Copy specs directly into Cursor or Claude Code. Every spec links back to the original customer feedback as evidence. Linear, Jira, and GitHub integrations coming soon.

From market signal to product spec

Real reviews from PM tool users — turned into an implementation-ready spec by Obsidius.

Market signals

5 items

G2, TrustRadius & Capterra reviews

FeatureTrustRadius

“Lack of export capabilities. Lack of flexibility to build scoring equations.”

FeatureG2 Review

“We would like to see greater reporting and analytics capabilities to generate our own insights from the data.”

BugCanny Board

“We lack a visual, time-based overview… have to manually compile data to understand how votes evolve.”

Churn riskCapterra

“Today we have to manually generate reports so they can see the status of all ideas. This should be self-service.”

FeatureTrustRadius

“There are too many conflicting prioritization methods. It could be better tied to business goals.”

Generated spec

L effort

Smart Feedback Analytics & Priority Scoring

User stories

Product Manager

I want feedback automatically prioritized by frequency, recency, and urgency

Operations Lead

I want self-service dashboards that show feedback trends over time

Acceptance criteria

Priority scores auto-calculated from frequency, recency, and urgency weights
Dashboard provides time-series view of feedback trends by category
Reports exportable as CSV with human-readable column headers

Based on 5 market signals

Evidence linked

See it in action with your own feedback

Paste your customer feedback and watch Obsidius turn it into specs in seconds.

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