Product guide / Matrices
the comparison grid, built for you
Ask for the map, not another answer.
Describe the portfolio and the vertical, and an agent builds the grid to compare it: the columns that matter, the workflow those columns imply, and a proposed row for every candidate — with the evidence behind each cell.
| Candidate | Status | Value | Effort | User need | Evidence | Risks | Decision | Owner |
|---|---|---|---|---|---|---|---|---|
| AI-Powered Query Suggestions | shipped | high | medium | Reduce time users spend writing complex queries | Support tickets citing query difficulty up 40% | Model hallucinations returning wrong suggestions | Ship with confidence threshold gating | Platform Team |
| Real-Time Dashboard Alerts | building | high | medium | Notify users when KPIs breach thresholds | Requested by 14 enterprise accounts in QBRs | Alert fatigue if defaults too sensitive | Build with smart cooldown periods | Growth Engineering |
| CSV Bulk Data Import Wizard | validated | high | low | Onboard data without engineering help | 60% of trial drop-offs at data connection step | Malformed CSVs causing silent data errors | Validate schema before commit; show diff preview | Onboarding Squad |
| Role-Based Access Control v2 | shipped | high | high | Admins need granular permission scoping | RBAC gap blocked 3 enterprise deals in Q2 | Misconfigured roles could expose sensitive data | Launched; monitor audit logs for anomalies | Security Team |
| Embedded Analytics SDK | building | high | high | Let customers embed charts in their own apps | 5 design partners confirmed intent to use SDK | SDK versioning and breakage on updates | Build v1 with iframe fallback option | Platform Team |
| Slack Digest Integration | validated | medium | low | Surface weekly metric summaries in Slack | Slack listed in 8 of 10 user-research sessions | Token revocation breaking scheduled digests | Scope to weekly summaries only for v1 | Integrations Team |
| Cohort Retention Analysis Module | idea | high | medium | Track user cohort behavior over time | Competitors offer cohort views; gap noted in demos | Complex UI may confuse non-analyst users | Needs UX prototype before committing to build | Product Team |
| White-Label Report Exports | idea | medium | low | Agencies need branded PDF reports for clients | 3 agency customers requested in NPS comments | Custom branding scope can grow quickly | Validate demand before scheduling sprint | Product Team |
| In-App Onboarding Checklist | shipped | high | low | Guide new users to first meaningful insight | Activation rate up 22% in A/B test | Checklist dismissed too early by power users | Shipped; add skip logic for experienced users | Growth Team |
| Data Freshness Indicators | building | medium | low | Show users when underlying data was last synced | Stale data complaints in 12 support tickets | Misleading timestamps if sync jobs fail silently | Show last-sync time with staleness warning badge | Data Infra Team |
| Custom Metric Formula Builder | stopped | medium | high | Let analysts define calculated metrics via UI | Only 4% of users had asked for formula editor | High complexity; low adoption likely | Stopped; SQL editor covers advanced use cases | Product Team |
| Multi-Workspace Data Federation | idea | high | high | Enterprises need cross-workspace unified views | Raised by 2 Fortune-1000 prospects in discovery | Data isolation and compliance complexity | Park until 5+ accounts confirm willingness to pay | Platform Team |
| AI-Powered Dashboard Insights | building | high | high | Analysts need to surface anomalies and trends without writing custom queries every time. | User interviews (n=18): 14 cited manual reporting as top pain point; NPS drag of -12 pts. | Model accuracy below 85% will erode trust; data privacy compliance adds scope. | Build in-house using existing data lake; defer third-party ML vendor to Q3 review. Effort is ~10 weeks across ML pipeline, model training, and UI. Rated high value on time-to-insight, from hours to minutes, and on its weight in competitive demos. | Head of Product |
| Native Salesforce CRM Connector | idea | high | medium | Sales-led teams need CRM data in Nexus without manual CSV exports. | Lost-deal analysis: 11 of 30 enterprise losses in Q1 cited CRM integration gap. | Salesforce API rate limits may affect sync reliability at scale; ISV certification adds 4 weeks. | Prioritize in Q3; assign a dedicated integration engineer and begin Salesforce ISV certification. Effort is ~5 weeks for OAuth, field mapping, and sync scheduling. Rated high value on the 40+ enterprise prospects blocked on it, an estimated $1.2M ARR opportunity. | Engineering Lead — Integrations |
| Scheduled Report Delivery | validated | medium | low | Executives need automated weekly and monthly reports delivered to their inbox without logging in. | Feature request logged 34 times in support portal; mentioned in 7 of last 10 QBRs. | Email deliverability and formatting across clients; data freshness SLA must be defined. | Build and ship in Q2 alongside the dashboard refresh, on the existing SendGrid integration. Effort is ~3 weeks for the renderer plus scheduler. Rated medium value: real stickiness for non-daily users and executive churn cover, but no direct revenue. | Product Manager — Retention |
| Mobile App Read-Only Mode | stopped | low | high | Field sales and executives need read-only dashboard access on mobile devices. | Requested by 12% of surveyed users; usage data shows less than 5% of sessions from mobile browsers. | High effort for limited engagement uplift; creates ongoing mobile engineering overhead. | Stopped; revisit only if mobile session share exceeds 15% or a strategic partner requires it. Effort was ~16 weeks minimum for native or React Native, with ongoing mobile engineering overhead. Rated low value: high perceived value in demos, little revenue impact. | Head of Product |
Where this helps
Ask ten people to rank the same portfolio and you get ten defensible rankings. Without a shared grid, prioritization resolves to whoever argues hardest that week, and the company pays for it a quarter later.
The question it puts in front of you
Across this portfolio, which bets earn the next quarter — and which do we stop?
Where judgment belongs
You set the criteria, own the cells, and make the call. An agent can draw the map; what the map means stays with the people accountable for the quarter.
What gets prepared for you
An agent generates the columns that fit the vertical, derives the workflow stages from them, and proposes a row per candidate — a column being one question asked of every row at once, not another single answer.
Strategy & decisions
How a portfolio gets mapped.
Ask for the grid in Chat: the agent proposes the columns, the stages, and the rows in one pass.
Or start from one of fourteen typed templates and adapt it — the vertical ones assume the vocabulary, so a grant programme does not start from a startup grid.
Compare across user need, value, effort, evidence, risk, and owner in table or Kanban, versions preserved.
Challenge any cell against its evidence, then export the filtered view as CSV.
Matrices in the real world
One map the company argues from, instead of twelve private answers.
It happens in three passes, and the order is the point. The agent picks the columns that fit your vertical — user need, value, effort, evidence, risk, owner. It reads the workflow stages out of those columns. Only then does it work down the rows, answering every column for every candidate. Rows arrive as proposals: the agent draws the map, you ratify it.
That map is also what makes every other agent worth having. An agent working from a shared grid is reasoning over the best data you own. The same agent in a private thread is reasoning over one person’s memory of it.
What holds up
What it does well, and what it was never meant to do.
Constraints are a design position, not an apology. Everything on the left ships today; everything on the right we decided against.
What you can rely on in Matrices
- Ask in Chat and an agent builds the grid: columns, stages, and proposed rows.
- Workflow stages follow the columns, and stay in step when you change them.
- Fourteen ready-made grids, and the list says who they were built for. Operating: Bet List, Product Portfolio, Goal Loops, Anticipation Radar, Outcome Tracker. Capital: VC Thesis Matrix, Term Sheet Review, Legal DD Matrix, Portfolio Monitoring, Fundraising Round. Institutions that do not raise venture money: Donor & Grant Pipeline, Grant Compliance, Stakeholder Map, Spinoff Commercialization.
- CSV export follows whatever you have filtered.
What we chose not to build
- Agent-generated rows arrive as proposals. Nothing is approved, published, or ranked as final by an agent.
- A Matrix is not a parallel database or a spreadsheet replacement.
- A Matrix does not replace Pipeline, Portfolio, or Initiatives.
- Room policy can block downloads.
Outputs & automation
Filtered CSV when Room and company policy allow it
None of this is trapped in the interface. The same API and CLI that produce these outputs are how you drive Operalta from your own tools — a script, a terminal, or another product entirely.
Works with
Where Matrices hands the work on.
Decisions rarely stop where a product does. These are the guides that pick the work up next.
For your company
See how Operalta fits your company.
Bring one current decision or process. We will map it together.