All modes · Audience: Investor
CODA Requirement Intelligence
Turning operational signals into governed software execution.
CODA Requirement Intelligence turns operational signals into governed software execution.
From logs, grievances, policies, documents, requirements, and codebase evidence into classified control gaps, correlated candidates, implementation reality checks, and human-confirmed engineering decisions.
Current environment snapshot — includes live requirement and candidate batch counts from this environment. · File-backed candidate batches — not production authorization. · Safe fallback metrics; no full log scan on page load.
Operational complexity and compliance pressure are rising while engineering capacity is flat. Organizations that cannot reconcile signals, requirements, and code will accumulate invisible control debt — until audit or incident exposes it.
Millions of operational events hide recurring control and workflow failures.
HR and compliance issues describe system gaps — not language problems to sanitize.
Policy obligations rarely map cleanly into engineering backlogs.
Procedures and finance docs hold controls that never become testable requirements.
Backlog tables go stale; weak acceptance criteria look planning-ready.
Partial implementation is invisible if you only read the requirement row.
CODA's moat is a universal operating intelligence layer: new sources become adapters, not new engines. Cross-source correlation and codebase reality checking sit behind an evidence-only governance posture.
Current environment snapshot — safe fallbacks when live counts are unavailable.
New sources become adapters, not new intelligence engines.
Functional and operational patterns at scale.
Control failures → system-control recommendations.
Obligations and approval language.
Procedure and requirement-like content.
Indexed backlog — intent, not proof of implementation.
Future adapters only — not a new intelligence engine.
Origin of the signal — log, grievance, policy, document, requirement.
Interpretation — control gap type, risk domain, sensitivity.
Pattern tracking across time and routes.
Relationships across sources — one cluster, one control story.
Confidence-scored recommendation — not approval.
Confirmation of high-impact decisions — not manual re-classification.
Related signals across reservoirs converge on one control story — not duplicate tickets.
One cluster · one diagnosis surface
Improve existing requirement or create tightening requirement.
Human confirmation required — financial-control sensitivity.
Automated diagnosis complete — humans confirm high-impact decisions.
System recommendation needs confirmation because this is a financial-control signal.
Requirements describe intent. The codebase reveals reality.
Code evidence is not human acceptance. The requirement row is not final proof of implementation.
Independent payment approval should exist with separation of duties.
What the requirement says should exist.
Models, views, services, templates, tests in repo.
Partial / likely implemented / missing controls / needs tests.
Suggested controls not evidenced in code.
Improve requirement, tighten, attach evidence, or audit.
| Score | Band | Meaning |
|---|---|---|
| 90–100 | Auto-ready recommendation | Still not approval. Low/medium risk only. |
| 80–89 | Guided confirmation | Strong diagnosis; sensitive domains still need explicit confirmation. |
| 60–79 | Human review required | Ambiguous requirement or codebase evidence. |
| Below 60 | Defer / insufficient evidence | Gather more context before backlog action. |
Financial, HR/grievance, security, and compliance signals always require confirmation before persistence or draft creation — even at high confidence.
CODA performs the diagnosis. Staff confirm, link, defer, dismiss, or use explicit promote for drafts.
Human review means confirmation of the system's diagnosis, not manual re-classification.
Accept the system recommendation after reviewing evidence.
Connect the signal to an existing requirement when the match is clear.
Persist source evidence without changing requirement status.
Only through explicit promote flow — never silent creation.
Send to the correct owner when evidence is incomplete.
Mark as not actionable without deleting source data.
No silent automation. No automatic approvals. High-impact decisions stay human-confirmed with a full audit trail.
RequirementPrompt artifacts — no automatic field mutation.
GQI, Prompt Packs, and Control Cycle do not authorize production.
Feature flags and staff-only routes — not autonomous rollout.
Pilot settings can redact HR/grievance text in reports.
Evidence history and reconciliation decisions are retained.
governance_state_change: forbidden production_activation: blocked approval_gate: NOT_IMPLEMENTED
Primary evidence is the working route — screenshots are optional for PDF/offline export.
Command center for backlog health, intelligence links, and AI_SYSTEM tooling.
Open requirements hub/requirements/
Hub cards linking to candidate review, observatory outputs, and staff tools.
File-backed candidate batches from Source Observatory and correlation.
Open candidate review/ai_services/source-candidates/
Batch list, grouped view toggle, unresolved vs attached counts.
Active staff pilot batch when available; otherwise start from the queue.
Open candidate review queue/ai_services/source-candidates/
Grouped review cards, human-readable actions, pilot guardrails banner.
Automated control gap diagnosis on group and candidate detail.
Open grouped review (select a batch)/ai_services/source-candidates/?view=groups
Automated Control Diagnosis block, suggested system controls, live route to codebase reality.
Compare requirement intent to codebase evidence; staff reconciliation queue.
Open reconciliation queue/ai_services/requirements/implementation-audit/reconciliation/
Audit status, matched paths, missing controls, reconciliation decisions.
Open a requirement to view evidence history, GQI, and prompt packs.
Sample requirement CODA0008296/requirements/8296/
Evidence history list, AI_SYSTEM artifacts, unchanged requirement fields after evidence attach.
AI-generated pitch center for staff (separate from this flagship page).
Open presentation center/portfolio/requirements/
Pitch generation form — login required; does not mutate requirements.
Curated demo command center with live links (you are here).
Demo mode deck/portfolio/requirement-intelligence-platform/demo/
Live evidence cards, presenter notes, demo path — links over screenshots.
These working routes become the controlled staff pilot path: every step produces evidence, but no step silently approves, mutates, or activates production behavior.
Controlled staff pilot — not autonomous production.
Reads selected source reservoirs; produces JSON/report.
No database mutation on requirements or logs.
Clusters related signals across sources.
Evidence optional; no auto-promote.
Staff review grouped by requirement, topic, or control pattern.
Defer/dismiss updates review_state only.
Automated diagnosis with suggested system controls.
Diagnosis is not proof or approval.
Attach to existing requirements via RequirementPrompt.
Does not mutate Requirement fields.
Compare requirement text to codebase paths.
Code evidence is not human acceptance.
Staff queue for audit vs backlog decisions.
Records decision — not production authorization.
Pilot metrics and findings for staff learning.
Report-only; production_activation blocked.
Investors should see defensible operating intelligence — faster conversion of incidents and policies into governed engineering work, with backlog discipline and compliance defensibility.
Fewer orphan signals and duplicate requirements.
Incidents, policies, and logs become governed engineering work.
Codebase reality is checked before commitment.
New sources are adapters, not new engines.
Evidence-backed, human-confirmed decisions.
Grievances and operational failures become system controls, not vague tickets.
Open working pages in order — each link is read-only or staff-governed review.
Hub linking observatory, candidates, and staff tools.
/requirements/intelligence/
Open
Grouped candidate review and control gap diagnosis.
/ai_services/source-candidates/
Open
Implementation audit findings vs requirement truth.
/ai_services/requirements/implementation-audit/reconciliation/
Open
AI-generated pitches (login) — separate from this flagship page.
/portfolio/requirements/
Open
Flagship demo command center with live evidence links.
/portfolio/requirement-intelligence-platform/demo/
Open
Controlled production staff pilot with guardrails.
Bulk attach / merge hints if reviewers need throughput.
Google Drive adapter discovery (adapter only).
Canonical assessment model if UAT proves persistent fields.
Controlled status mutation only after explicit governance approval.
Roadmap does not change current approval boundaries — governance_state_change remains forbidden.
CODA closes the loop.
What happened in operations.
What policy required.
What the backlog claimed.
What the code actually implemented.
What humans approved.
This is the difference between documentation and governed execution.