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Project management for the AI era

AI Solved Coding.

SignalsAI Solves Delivery.

AI made coding faster but delivery speed hasn't adopted.

The first AI platform that makes your software delivery faster from planning to day to day delivery.

PR-Level AI Attribution Capacity Planning Intelligent Task Routing Delivery Genie Feedback Loop Automation Cycle Time Correlation Risk Radar Signals Brain Large AI PR Detection Human Edit on AI Code Committed vs Delivered Agentic Coordination

AI Coding Speed ≠ Delivery Speed.SignalsAI is the multiplier.

The bottleneck has shifted from Coding to Planning, Co-ordination and running delivery.

Pre AI Era

PlanningManualCapacity, scope, and sprint planning done by hand across spreadsheets and meetings.
CodingManualEngineers write and review every line — no AI acceleration in the loop.
ExecutionManualStandups, status pings, risk fire drills, and PM coordination consume the calendar.
FeedbackManualRetros, reports, and learnings compiled manually — often after the sprint ends.

AI Era

PlanningManualStill manual — handoffs and alignment haven’t sped up with AI coding tools.
CodingAutomatedAI assistants shrink implementation time — the only phase that got meaningfully faster.
ExecutionManualCoordination, risk, and PM work still run on humans — now the longest part of delivery.
FeedbackManualRetros and reporting still assembled by hand — insights arrive too late to change the sprint.

1.2x faster delivery

Signals Era

PlanningAutomatedCapacity, routing, and commitment guardrails run by Signals agents.
CodingAutomatedAI coding speed preserved — with full delivery context on every change.
ExecutionAutomatedAgentic PM, risk radar, and coordination — no status chasing.
FeedbackAutomatedRetros and committed-vs-delivered insights drafted before the meeting starts.

Planning, coordination, and delivery loops — completely automated by Signals.

4x faster delivery

How SignalsAI Works

The intelligence layer formodern software delivery.

Built for humans and agents across planning, execution, and delivery — from systems of record to agentic orchestration.

04IntelligenceAgentic delivery
The differentiator

Agentic delivery intelligence

Becomes the orchestration layer — agents detect risk, coordinate, and follow through.

Live · Agents
Agentic Project Coordination Risk Detection Predictive Insights Delivery Intelligence Autonomous Follow-through
03The differentiatorContext
The differentiator

Organizational context & memory

Connective memory across your delivery stack — not another dashboard.

Cross-System Memory Project Intelligence AI + Human Signals

Delivery context graph — one connected memory across Jira, GitHub, Slack, and AI activity so agents act with full situational awareness.

02VisibilityObservability

Visibility & observability

Real-time visibility across engineering execution.

Competitors are here
Delivery Visibility Workflow Observability Execution Monitoring Team Health
01Source systems / systems of recordIntegration

Workflow tools SignalsAI integrates with

Plugs into fragmented systems where work already happens — no rip-and-replace.

Jira GitHub Slack Microsoft Teams GitLab Linear Azure DevOps Jenkins Asana Notion Confluence GitHub Copilot

From systems → to visibility → to context → to agentic intelligence

End-to-End Delivery

One loop. No manual steps.

SignalsAI runs the entire delivery loop — planning, execution, feedback — so your team never has to push the process forward.

01

Planning

  • Capacity planning

    Load-balanced sprints from real velocity and availability.

  • Intelligent task routing

    Right engineer, right skill — dependencies included.

  • Sprint commitment guardrails

    Overcommit and blocker risks flagged before kickoff.

02

Execution

  • Runs the sprint

    Progress tracked automatically from real activity.

  • Catches risks early

    Blocks and deadline conflicts surface days early.

  • Auto-resolves & escalates

    Right person, full context — no status pings.

03

Feedback Loop

  • Reports write themselves

    Summaries from committed vs. delivered data.

  • PR-level AI attribution

    AI %, human edits, cycle time — per pull request.

  • Patterns feed next sprint

    Insights land before the retro meeting starts.

What SignalsAI owns

One platform. Three phases.

Every capability maps to planning, execution, or the feedback loop — the same story, end to end.

Planning phase

Capacity-aware planning that routes work before the sprint starts.

  • Capacity planning from real velocity

    Sprint load balanced against availability, WIP, and historical throughput — not gut feel.

  • Intelligent task routing

    Tasks assigned by skill, ownership, and dependency graph across teams and repos.

  • Commitment guardrails

    Overcommit, hidden dependencies, and blocker chains flagged before kickoff.

  • Cross-tool sprint intake

    Jira, Linear, and Notion work unified — no duplicate tickets or stale scope.

Capacity · Sprint 25Balanced
Auth team32 pts capacity · 28 committed
Platform teamOver by 4 pts

Intelligent routing

  • →AUTH-241 → Arjun (OAuth owner)
  • →API-305 → Priya (blocked by DS-118)
PR intelligence · Sprint 24

AI usage correlated to cycle time & quality

Per PR

2.4d

Avg cycle (high AI)

11%

Change fail rate

0.9d

Avg cycle (low AI)

PRAI%Human editLinesCycleFail%Signal
PR-1842

OAuth token refresh middleware

91%12%12404.2d18% Large AI PR
PR-1839

Rate limiting for public API

44%68%1861.1d4%
PR-1831

Session expiry interceptor

72%41%4122.8d11% High AI, rising fail rate
PR-1827

PKCE flow edge case fix

22%94%640.9d2%

Insight: PRs with 800+ lines and 85%+ AI correlate to 2.1× longer review and 3× higher fail rate this sprint.

Execution phase

The sprint runs itself — with PR-level intelligence on every change.

  • PR-level AI vs. human attribution

    Every pull request: AI %, human edits on AI code, lines changed — not sprint-level guesses.

  • Correlated to cycle time & quality

    See how AI-heavy PRs map to lead time, change fail rate, and review lag in real time.

  • Large AI PR detection

    Flags outsized AI-generated changes that spike review time or defect risk for the team.

  • Mid-sprint risk radar

    Deadline conflicts, blocked chains, and velocity drops caught days before review.

Feedback loop phase

Retros and reports that close the loop — automatically.

  • Committed vs. delivered tracking

    Measures what the sprint promised against what shipped — every sprint, no manual rollup.

  • Auto-drafted sprint retros

    Retros drafted from delivery data before anyone asks — patterns ready for the meeting.

  • Delivery outcomes tied to AI usage

    Connect AI adoption to throughput, quality, and team health — not vanity percentages.

  • Patterns feed the next planning cycle

    Insights from this sprint inform capacity and routing in the next — the loop closes.

Feedback loop · Sprint 24Closed

Committed vs delivered

8 tasks committed · 8 / 8 shipped ✓

  • ▲

    Large AI PRs slowed Auth team

    PR-1842 · +2.1d avg review · feeds Sprint 25 capacity

  • ✓

    Human-heavy PRs shipped fastest

    0.9d avg cycle · 2% fail rate

  • ↻

    Routing rule updated for OAuth work

    Pattern applied to Sprint 25 planning

Sprint retro → Auto-drafted · loop closed ✓

Software Delivery is no longer about managing cards on a board. It's about orchestrating intelligence.

8+

hours saved per engineer per week

Not from working faster — from eliminating coordination work that shouldn't require an engineer at all.

73%

of PM work that doesn't need a human

Task creation, status tracking, sprint reporting — automated from real data.

2.4d

average risk detection lead time

That's your window to fix issues before the sprint review surfaces them.

Trusted By

Teams Building the Future

Join innovative companies transforming engineering delivery with AI-powered workflows

Integrations

Works inside the stackyou already have.

No ripping and replacing. SignalsAI connects to your existing tools in minutes.

GitHub GitLab Bitbucket Azure DevOps Jira Linear Notion Confluence Slack Cursor GitHub Copilot Claude Code Atlassian Jenkins Travis CI Microsoft Teams AWS CodeCommit ClickUp Asana CI/CD

Enterprise-Grade Security & Compliance

Your data security is our top priority. We maintain the highest standards of compliance and security.

ISO 27001

Certified information security management system ensuring comprehensive data protection

SOC 2 Type II

Independently verified controls for security, availability, and confidentiality

Trusted by enterprises worldwide. Our compliance certifications demonstrate our commitment to protecting your sensitive data and maintaining the highest security standards in the industry.

Less coordination. More shipping.

Book a 30-minute demo. We'll show you exactly what SignalsAI sees in your stack — and what your team gets back when delivery runs itself.

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