Product
The control plane for software delivery.
Alan gives engineering teams one system for shared context, agent orchestration, verification, and human control — from plan to production.
- Context layerShared memory across repos, tasks, and agents
- Agent orchestrationRoute work across Codex, Cursor, Claude Code, and CI
- Sessions and sandboxesIsolated cloud environments for every serious run
- VerificationCI, QA, and review inside the agent loop
- Control and checkpointsHuman judgment at the moments that matter
- Tasks and boardsSprint boards where agents are first-class contributors
- IntegrationsGitHub, trackers, CI, chat, and the tools you already run
- ObservabilityUnified visibility across every agent run and outcome
Outcomes
- Agents stop rediscovering tribal knowledge every session
- Humans and agents share the same source of truth
- Decisions stay attached to the work they shaped
How it works
- Artifacts and events flow into a persistent context graph as work happens.
- When a task starts, Alan retrieves the relevant history for that repo, team, and outcome.
- Results write back so the next turn inherits what just shipped or failed.
Outcomes
- The right agent for the job without chat-hopping
- Long-running work that survives restarts and handoffs
- A single board where humans and agents are teammates
How it works
- A task is scoped with acceptance criteria, repos, and constraints.
- Alan assigns an executor and environment, then tracks progress through checkpoints.
- Failures become recoverable state instead of dead chat threads.
Outcomes
- Fewer “works on my machine” agent failures
- Parallel work without colliding branches or secrets
- Clear lifecycle: start, pause, resume, stop, archive
How it works
- A session binds the task, repository, agent profile, and runtime target.
- Sandboxes provide an isolated workspace for code changes and tool use.
- Operators can reconnect, pause, or shut down without losing the task record.
Outcomes
- Broken work fails early while context is still hot
- Repair cycles happen before humans spend attention
- Ship decisions rest on evidence, not vibes
How it works
- As agents produce changes, Alan triggers the relevant verification path.
- Failures come back with enough context to diagnose and re-run.
- Green checks and review notes attach to the task before merge.
Outcomes
- High-impact actions require explicit approval
- Auditability across agent actions and outcomes
- Teams move fast without surrendering control
How it works
- Policies define which steps need a human gate.
- Agents pause with a clear ask, context, and recommended next action.
- Approvals and rejects become part of the durable task history.
Outcomes
- One place to see what is running, blocked, and done
- Assignments that include agent profiles, not just people
- Less status theater in Slack and standups
How it works
- Work is structured as tasks, subtasks, and epics with clear owners.
- Agent sessions report progress back onto the same cards.
- Comments, decisions, and artifacts stay attached to the work item.
Outcomes
- No rip-and-replace of the tools teams already trust
- Signals from many systems land in one workflow
- Outbound updates keep stakeholders in sync
How it works
- Connect source control, trackers, and automation endpoints once.
- Triggers and webhooks create or advance Alan tasks.
- Results write back as PRs, comments, checks, or messages.
Outcomes
- Faster debugging when an agent goes sideways
- Shared visibility for eng leads and IC owners
- A trail from intent to merge for audits and retros
How it works
- Every session records prompts, tool use, and state transitions that matter.
- Task timelines surface decisions, blockers, and validation results.
- Teams can resume from evidence instead of reconstructing chat history.
See the system behind the agents.
Book a demo and walk the control plane: context, orchestration, verification, and checkpoints on your stack.