Keep your agents on budget, on time, and on spec.
Lumo is the project tracker for teams that ship with AI. Meter every token and hour your agents burn — and verify they built the right thing before it reaches your users.
Built on techniques published research shows work — reusing past-run experience cut agent cost a mean 31.8%, with ≤0.2% quality loss, in controlled trials.1
The percentages below are effects measured in published research on the techniques Lumo is built on — not Lumo's own benchmarks. See the studies.
Run AI work like a team, not a black box.
Token & cost metering
Every agent run is metered to the token — broken out by model and token type. See live spend per task, per agent, and per sprint.
Time on task
Know which work is fast, which is stuck, and which to re-route.
Boundary guardrails
Left unguarded, agents take harmful out-of-scope actions in most red-team trials; pairing rules with an explicit rationale cuts that to roughly a third — 65% → 19%.6 Lumo classifies every crossing across 9 categories by type and severity, gates CI on catching every one, and stops the irreversible ones before they merge — modeled on the collateral-damage3 and minefield4 checks from agent-safety benchmarks.
Verifiable acceptance
Write crisp acceptance criteria once. Agents can only mark a task done when every criterion provably passes — and non-deterministic checks report cross-run agreement, not one lucky pass.5
Context engineering
In published trials, structured context-trimming cut filler ~39% while raising task quality +2.8%.2 Lumo assembles each run from the sources that matter — Slack, specs, docs, Figma, PRs — and trims the rest.
Lineage & memory
Reusing prior-run experience cut agent cost a mean 31.8% in published trials.1 Lumo links every decision, source, and run so agents reuse what worked — and you can trace why.
Sprints & milestones
Roll work into sprints with burn-up, risk, and AI-written summaries — the planning layer your humans already know.
Plan it. Dispatch it. Verify it.
Break work into verifiable tasks.
Define what "done" means up front. Each task carries acceptance criteria your agents — and your reviewers — are held to.
Point your agent at a task. It drives Lumo.
One command runs the whole workflow over Lumo’s CLI — attach, load context, verify — and a task can’t be called done until every acceptance check provably passes.
Questions, answered.
Put your agents on the record.
Start tracking tokens, time, and verified work in minutes. Free for your first five seats.
Start for free- 1Guo et al., experience-injection + early-stopping on SWE-bench Verified (ACL 2026 Findings). arXiv:2601.05777
- 2SkillReducer — taxonomy-driven context compression across 55k skills. arXiv:2603.29919
- 3AppWorld — collateral-damage checks for agent actions. arXiv:2407.18901
- 4ToolSandbox — stateful “minefield” evaluation of tool use. arXiv:2408.04682
- 5LLM-judge reliability under cross-run agreement (pass^k discipline). arXiv:2603.02473
- 6Anthropic — Model Spec Midtraining: pairing rules with an explicit rationale reduces agentic misalignment (2026).
Figures above are effects measured in published research on the techniques Lumo is built on — not Lumo's own benchmark results.