AI agents see code, not intent
Cursor and Copilot read your repo. They have no idea what the feature is for, who asked for it, or what was decided in the product spec review.
Private beta — building in the open
AI agents at every step of the SDLC
Product owners drafting specs. Leaders planning capacity-aware roadmaps. Designers connecting Figma. Engineers shipping code. Every AI agent in Codara reads from the same shared product context — so the work fits the product, end to end.
Product overview
The problem
Your AI agents are flying blind
AI-assisted development is everywhere — and yet the agent is the least informed person on the team. It sees the repo, maybe a few MCP feeds, and a one-paragraph user story. Everything that makes the work matter — the goals, the product spec, the design rationale, the decisions — lives elsewhere.
Product context lives in tools the agent can’t read
Product specs in Notion, designs in Figma, decisions in Slack threads, tickets in Jira. The information the AI needs most is spread across systems it has no access to.
Engineers re-paste context every prompt
You end up the human bridge: copying summaries, design notes, and rationale into prompts so the AI doesn’t go off the rails. Repeat per story, per agent.
How it works
One unbroken context chain — from initiative to diff
Codara isn't a chatbot stapled to a ticket system. It's a workspace designed so the AI Coding Agent inherits every decision upstream of the story.
- Step 1
Initiative
A funded bet on a product outcome — what we’re trying to change for users and the business.
- Step 2
Product spec
Problem framing, success metrics, scope, and acceptance-test plan — drafted by the PM Initiative Agent, edited by a human.
- Step 3
Design
Flow maps, wireframes, and design decisions linked to the product spec so trade-offs are recorded, not lost.
- Step 4
Technical design doc
Architecture decisions, data model, API surface, security posture — the technical why behind each epic.
- Step 5
Story
Groomed work item with acceptance criteria, sub-tasks, and links back through the whole chain above.
- Step 6
AI Coding Agent
Reads everything upstream — not just the story. Produces a diff that respects the product intent, not a guess from a prompt.
The chain works for every role, not just engineering. Product owners get an Initiative Agent that drafts specs and tests feasibility. Leaders get a Capacity & Planning Agent that builds roadmaps from real estimates. Designers get an agent reading their Figma. And by the time the Coding Agent writes a diff, it already has every upstream artifact in its working memory — no 2,000-token prompt required.
One platform
Everything the SDLC needs — together
Project management, collaborative documents, query language, and Git integration built as one product, not stitched together.
Configurable workflows
Issue types, statuses, transitions, and approval gates that match how your team actually works. No rigid templates.
Built-in collaborative documents
Real-time collaborative editor backed by Y.js, with version history and deep links between product specs, engineering proposals, and issues.
CQL — Codara Query Language
30+ fields, operators, and functions. Save any view; share it as a link.
Sprint planning + boards
Kanban, scrum, capacity, and burndown — natively wired to your issues, code, and docs.
Deep Git integration
Branches, pull requests, commits, and continuous-integration checks link to issues automatically. Pull-request risk scored in context.
Enterprise-ready by default
SAML SSO, SCIM provisioning, MFA, IP allowlisting, full audit log, Postgres row-level isolation.
AI agents
An AI agent for every role — sharing one context
Product owners get an Initiative Agent for spec drafting and feasibility. Leaders get a Capacity & Planning Agent that builds roadmaps from real team estimates. Designers get an agent that reads Figma. Engineers get a Coding Agent that inherits all of the above — every artifact upstream is in its working memory, with humans approving at each handoff.
SDLC Pipeline Agents
Triggered by workflow transitions
- PM Initiative Agent — Helps product owners go from rough idea to a real product spec — drafting success metrics, stress-testing feasibility and practicality, and checking alignment with the broader product strategy.
- Epic Decomposition Agent — Breaks initiatives into technical epics with architecture sketches, dependencies, and the trade-offs that informed them.
- Design Agent — Connects to Figma so the platform actually understands the designs — linking frames to stories and exposing design rationale to downstream agents.
- Story Agent — Generates groomed stories with acceptance criteria, sub-tasks, and estimates — pulling from the spec, the design, and prior decisions.
- Coding Agent — Produces code diffs, tests, and documentation from story specs — every diff awaits review.
Continuous Intelligence Agents
Always-on SDLC insights
- Capacity & Planning Agent — Builds roadmaps from real team capacity and historical estimates so leaders see the true effort and timeline — and miss fewer deadlines.
- Sprint Intelligence — Proactive risk alerts, burndown analysis, and daily digests so engineering managers stop chasing status.
- Story Quality Review — Flags vague scope, missing acceptance criteria, and backlog gaps before sprint planning.
- Deployment Readiness — Pre-release checklists, change-impact analysis, and rollback risk assessment.
- Pull Request Intelligence — Change risk scoring, security hotspot detection, and pull-request-trend analytics for engineering leaders.
Human-in-the-loop is a design constraint, not a setting.
Every AI-generated artifact — a product spec, a story, a diff, a decision — surfaces as a proposal that requires explicit human approval before it changes anything. Agents accelerate the team; they don't replace its judgement.
Who it's for
Built for the whole engineering org
Product owners
From rough idea to a real product spec with feasibility tested against the strategy.
- Initiative Agent drafts specs, metrics, and acceptance plans
- Feasibility checks against the broader product context
- Live progress and outcome metrics on every initiative
Engineering & product leaders
Roadmaps grounded in real capacity. Status without status meetings.
- Capacity & Planning Agent for capacity-aware roadmaps
- Continuous risk + sprint health signals
- Pull-request-trend analytics across teams
Designers & engineers
Less project-management overhead. AI agents that finally have the context to help.
- Design Agent reads Figma and links frames to stories
- Coding Agent drafts diffs from the full upstream context
- Status updates write themselves from your activity
Building in the open
What's shipping next
Themes, not dates. We share progress as we go.
Shipping next
- AI Coding Agent v1
- Pull Request Intelligence
- Custom workflows
In design
- Slack two-way sync
- Custom dashboards
- Native time tracking
Exploring
- Marketplace for community agents
Questions, answered
Frequently asked
Why not just use Jira plus Cursor, Copilot, or Claude Code?
Those agents are excellent at what they see, but they only see the editor and the repo. They don't see the initiative the work belongs to, the product spec, the design rationale, or the technical design doc. So when a developer hands an agent a one-line story, the agent guesses — and you end up either pasting context into prompts manually or shipping code that misses the product intent. Codara closes that gap: every upstream artifact lives in the same workspace as the story, so the Coding Agent inherits the full context of why the work matters before it writes a line.
Is Codara only for engineers?
No. Codara has an AI agent for every role in the SDLC. Product owners get an Initiative Agent that drafts specs, tests feasibility, and checks alignment with product strategy. Engineering and product leaders get a Capacity & Planning Agent that builds roadmaps from real team capacity and historical estimates — so timelines reflect what teams can actually ship. Designers get an agent that reads Figma. Engineers get the Coding Agent. Every agent shares the same product context.
How is Codara different from Linear?
Linear is a focused issue tracker; Codara is the full SDLC workspace — issues plus collaborative documents, CQL, sprint planning, AI agents that draft and code, and continuous-intelligence agents that flag risk. Linear gives you a fast inbox of work; Codara gives you the engineering OS where every piece of work carries its product context through to the AI agent that ships it.
How does this compare to GitHub Projects?
GitHub Projects is a thin layer over issues. It does not give you product specs, CQL, capacity-aware sprint planning, document collaboration, or AI agents. For engineering-only side projects it's sufficient; for funded teams it leaves you stitching Notion, Slack, and Linear back on.
Won't the AI agents take risky actions without permission?
No. Every AI-generated artifact — product spec, story, diff, decision — requires explicit human approval before it affects your project. The agents draft and analyse; humans decide. We treat human-in-the-loop as a design constraint, not a setting.
When can I try it?
Codara is in private beta. Join the waitlist and we'll roll out access as we work through onboarding. We're building in the open and will email you with progress milestones.
What does the data isolation model look like?
Every tenant lives behind Postgres row-level security tied to an org_id. Inter-tenant access is impossible at the database layer, not just the application layer. SAML SSO, SCIM provisioning, MFA, IP allowlisting, and a full audit log are available on day one.
Can we migrate from Jira?
Yes — Jira importer is on the roadmap as one of the first migration paths because it's the most common starting point. Reach out via the waitlist and we'll prioritise your migration as early access opens up.
Is Codara self-hosted or cloud-only?
Cloud-only. We're not planning a self-hosted edition — building one would split the engineering effort across two distribution models and slow down the product. If that's a hard requirement, Codara isn't the right fit.
Be early to Codara
We're rolling out access to early adopters. Join the waitlist and we'll email you with progress and access.
