Small team. Sharp tools. Real delivery.

See sprint risk before it becomes a missed deadline — inside Jira & Atlassian.

AgileOS AI Labs builds delivery-intelligence tools that surface sprint risk, spillover patterns, and team health directly from your Jira data — plus hands-on software engineering, data, and cloud services for enterprise teams.

5+Products in active development and R&D
6+Engineering & delivery service lines
3Locations we're building from
2024Founded
Coming soon to the Atlassian Marketplace
Built for Jira Cloud Jira Software Confluence 🔒 Secure by design
About us

Built by practitioners who ran the ceremonies, not just studied them.

AgileOS AI Labs was founded on a simple observation: Scrum Masters and Release Train Engineers spend more time chasing status updates and building slides than coaching teams. We've lived that problem from inside enterprise SAFe environments across telecom, semiconductor, and e-commerce delivery — and we built the AI layer we wished we'd had.

Today we design AI-native tools that plug directly into Jira and the Atlassian ecosystem, turning raw sprint data into decisions: where risk is building, which team needs support, and what a Scrum of Scrums actually needs to talk about this week.

That same practitioner discipline now extends well past agile coaching. Our engineering, data, and cloud teams deliver full-stack services tailored to the compliance, scale, and technical demands of each industry we serve — from SLA-bound release trains in telecom to validation-grade reporting in healthcare and audit-ready pipelines in banking.

Telecom
Semiconductor
E-Commerce & Retail
BFSI
Healthcare
Manufacturing

Built on real delivery data

Our dashboards are designed to read directly from live Jira data, not static mockups.

Practitioner-built

Designed by certified Scrum Masters and SAFe practitioners, not just engineers.

Fits your stack

Native Jira and Atlassian integration — no migration, no rip-and-replace.

Why teams look for this

The problems we're building AgileOS AI-SM to fix

Problem

Missed sprint commitments

Spillover creeps up sprint after sprint and nobody notices the pattern until it's a trend, not an incident.

Problem

Manual status reporting

Scrum Masters and RTEs lose hours a week building the same status slide from the same Jira boards.

Problem

Risk found too late

By the time a sprint's health shows up in a retro, the window to actually course-correct has usually passed.

How it works
1

Connect Jira

Install and authorize with OAuth 2.0 — read-only access to the projects and boards you already have permission to see.

2

We read your sprint data

Issues, sprints, boards, and changelogs are pulled live via Jira's REST API — no manual exports, no spreadsheets.

3

Get a scored, prioritized view

A configurable weighted model scores sprint risk and spillover so you know where to look first — not just a wall of charts.

Products

Two products. One mission: give delivery teams their time back.

Chrome Extension · In development

AgileOS AI-SM

A Scrum Master dashboard that lives inside Jira, built to surface sprint risk signals from your team's real sprint data.

  • Sprint risk scoring based on a configurable weighted model
  • Sprint-to-sprint performance comparison with KPI cards & trends
  • Reads directly from your Jira data — no manual exports
  • Lightweight interface designed for daily ceremony use
Join the early access list →
72% SPRINT HEALTH
Atlassian App · In development

Atlassian PowerKit

A set of admin utilities for teams running larger Atlassian estates — aimed at admins, RTEs, and platform owners who need more than the stock tooling.

  • Cross-board automation rules for multi-team programs
  • Bulk field, workflow, and permission management
  • Multi-project reporting rolled up to a portfolio view
  • Designed to scale across multiple teams and business units
Join the early access list →
Docs & resources

How our Jira & Atlassian integrations work

Reference material on the standards our tools are built on, how we handle your data, and what early access costs. Written for engineers, admins, and anyone evaluating a fit with their stack.

Integration reference
Guide

Authentication

Our tools authenticate against Jira and Confluence Cloud using OAuth 2.0 (3-legged) and Atlassian Connect app frameworks — the same standards Atlassian documents publicly for third-party apps. No credentials are stored outside Atlassian's own token flow.

Guide

Reading sprint & issue data

Dashboards pull from Jira's REST API (issues, sprints, boards, and changelogs) to compute metrics — nothing is entered manually and nothing is synced to a separate database beyond cached aggregates.

Guide

Webhooks & automation

Automation rules subscribe to Jira webhook events (issue updated, sprint started/closed) rather than polling, so boards reflect changes within seconds of them happening in Jira.

Guide

Permissions model

Access follows each user's existing Jira project permissions — a tool user can only see the projects and boards they're already permitted to see inside Jira itself.

Guide

Data residency

We don't duplicate your Jira instance. Reporting data is computed on read and cached briefly for dashboard performance; raw issue data isn't retained after a session ends.

Guide

Atlassian developer docs

For the underlying platform APIs our tools build on, Atlassian's own developer documentation is the authoritative reference — we link out to it rather than duplicate it, so it stays current as Atlassian updates their platform.

Reporting metrics glossary
Metric

Cycle time

Time from when work starts on an issue (first "In Progress" transition) to when it's marked done. Reported as a distribution, not just an average, since outliers skew a single number.

Metric

Throughput

Count of issues completed per time window (e.g., per sprint or per week), independent of story points — useful when point estimates vary in size or aren't used consistently.

Metric

Sprint spillover

Issues committed to a sprint that weren't completed by sprint end, carried into the next sprint. Tracked over time to spot planning or scope patterns.

Metric

Work in progress (WIP)

Number of issues actively in a non-done, non-backlog status at a point in time. High WIP relative to team size is one input into a risk score, not a judgment on its own.

Security & data privacy
Policy

What we access

Only the Jira/Confluence scopes required for the feature you enable (e.g., read issues, read sprints). We don't request write access unless a specific automation feature calls for it, and each scope is listed at install time.

Policy

Encryption

All traffic between your browser, our services, and Atlassian's APIs runs over TLS. Nothing is transmitted or stored in plain text.

Policy

No data resale

Your Jira data, issue content, and usage information are never sold or shared with third parties for advertising or any other purpose.

Policy

Deletion on request

Uninstalling the app or emailing us revokes access tokens and deletes any cached aggregates we hold within 30 days.

Pricing

Starter

Early access — contact us

For single teams trying AgileOS AI-SM on one Jira project.

  • Sprint risk scoring for one project
  • Sprint performance dashboard
  • Email support
Talk to us

Enterprise

Custom — contact us

For large Atlassian estates with compliance, SSO, or custom rollout needs.

  • Everything in Team
  • Dedicated onboarding & success engineer
  • Custom security review & SLAs
Talk to us

We're in early access — final published pricing will go live alongside our Atlassian Marketplace listing.

Industries we serve

Enterprise-grade delivery intelligence, tuned by sector

Our models and playbooks are calibrated against the delivery patterns, compliance demands, and ART structures of each industry we operate in.

Telecom

Multi-ART release trains coordinating network, OSS/BSS, and customer-facing platforms at carrier scale.

SLA-aware risk modeling

Semiconductor

Hardware-software co-development cycles with long lead times and tight tape-out deadlines.

Cross-discipline dependency tracking

E-Commerce & Retail

High-velocity squads shipping continuously through peak seasonal demand windows.

Seasonal velocity benchmarking

Banking & Financial Services

Regulated delivery pipelines requiring full auditability and change-control evidence.

Compliance-ready audit trails

Healthcare & Life Sciences

Quality-system-bound delivery with validation, traceability, and risk documentation built in.

Validation-grade reporting

Manufacturing & Industrial

Connected-product teams bridging embedded firmware, IoT, and enterprise software ARTs.

Firmware-to-cloud flow tracking
Services

Beyond agile — full-stack technology and delivery expertise

We pair our products with hands-on delivery, engineering, and data expertise to help enterprise teams modernize end to end.

Agile & Delivery
01 — Advisory

SAFe & Agile Transformation

End-to-end coaching for ARTs adopting SAFe, from PI Planning design to RTE enablement, led by certified practitioners.

02 — Integration

Jira & Atlassian Engineering

Custom Atlassian app development, Jira automation, and data pipelines that connect your tools into one delivery picture.

03 — Intelligence

AI Delivery Analytics

Custom-trained risk and flow-metric models tailored to your team's historical velocity and delivery patterns.

04 — Enablement

Scrum Master Co-Piloting

Embed AgileOS AI-SM into your ceremonies with guided onboarding and a dedicated success engineer.

05 — Training

Agile + AI Academy

Certification-track workshops on AI-augmented Scrum Mastery for teams and individuals entering the discipline.

06 — Support

Managed Rollouts

Dedicated implementation partners for large enterprise rollouts across multiple ARTs and business units.

Engineering & Technology
07 — Build

Custom Software Development

Full-cycle product engineering — architecture, web and mobile development, and API design for enterprise platforms.

08 — Platform

Cloud & DevOps Engineering

Cloud migration, CI/CD pipeline design, infrastructure-as-code, and platform reliability across AWS, Azure, and GCP.

09 — Data

Data Engineering & Analytics

Data pipelines, warehousing, and BI dashboards that turn fragmented enterprise data into a single source of truth.

10 — AI/ML

AI & ML Product Engineering

LLM application development, model fine-tuning, and MLOps for teams building AI features into their own products.

11 — Design

UI/UX & Product Design

Enterprise-grade design systems, usability research, and interface design for internal tools and customer products.

12 — Security

Cybersecurity & Compliance Advisory

Application security reviews, access governance, and compliance readiness for regulated industries.

Careers

Help us build reporting tools and delivery services for enterprise teams.

We hire across experience levels — from seasoned RTEs to graduates writing their first production code. Every open role below is live.

Engineering

Ship the product. AI integrations, Chrome extension architecture, Jira-native tooling.

Data & Quality

Turn raw delivery data into signal, and make sure every release meets the bar.

Delivery & Coaching

Bring SAFe and Scrum expertise to our customers and our own product roadmap.

Product, Strategy & Growth

Shape what we build next and help customers understand how it fits their delivery process.

Where we work

Three offices, one delivery standard.

From Hyderabad to the Middle East to Europe, our teams sit close to the customers and ARTs we serve.

🇮🇳

Hyderabad, India

Engineering & Product HQ

Core product, AI, and platform engineering team.
🇦🇪

Dubai, UAE

Middle East Delivery Hub

Customer success and enterprise rollout for the GCC region.
🇫🇷

Paris, France

European Operations

EU customer delivery, compliance, and partnerships.

Let's bring AI into your sprint room.

Whether you're evaluating AgileOS AI-SM, exploring PowerKit, or applying to join the team — we'd like to hear from you.

Contact AgileOS AI Labs