Put AI compute on a budget.
AI has become a runaway, unpredictable line item. Outlay attributes every dollar of LLM and coding-agent spend to the work you already plan — tickets, epics, roadmap — forecasts cost by scope, and lets you enforce a budget per program, reallocating compute to the work that matters most.
The question leadership keeps asking — finally answerable.
“What is this body of planned work costing us in AI, and are we on track?” Today's tools meter infrastructure — API keys, models, dashboards. Outlay meters the work.
Predictable delivery, by scope.
See exactly what each ticket, epic, and sprint costs in AI — and which work is about to blow its estimate — the way you already plan effort.
- →Cost per ticket, epic, sprint, and engineer, reconciled to the real invoice.
- →Estimate planned work from its requirements + design docs — budget an epic before you build it.
- →Forecast a quarter from its open scope, not from last month's bill.
- →Anomaly flags on the one ticket burning 10× its class — before it's a surprise.
Govern the fastest-growing line item.
Allocate AI spend to teams and cost centers, set budgets by scope, and get alerts before overspend — not a surprise invoice at month-end.
- →Allocation of every dollar to a team, cost center, and roadmap item.
- →Budget vs. actual with pace-based projection to end-of-period.
- →Pace-based guardrails that flag a scope trending over before the invoice lands.
A closed loop: attribute, forecast, guardrail.
Connect the tracker and AI tools you already use. Read-only to start — no app rewrite, no prompts leaving your environment.
Attribute
Every dollar of agent & LLM spend mapped to the ticket, epic, and roadmap it belongs to.
# tag / branch / PR → ticket
fix/PROJ-123 → PROJ-123 → Q3-stability
Forecast
Predict a quarter's cost from its open scope, the way you estimate engineering effort.
# open roadmap × per-class cost
Q3 forecast: $48k ± $9k
Guardrail
Pace-based alerts flag a team trending over before it blows through — not after.
# projected, not a hard cap
epic Q3-stability on pace $22k · over
Spend mapped to the work — projected on pace.
Every gateway, observability, and FinOps tool stops at an infrastructure tag. Outlay resolves the git context of each AI call back to the ticket — and budgets it like real work.
Illustrative. Flagged OVER early — driven by one outlier ticket at 11× its class median.
Enforce a compute budget by program — and reallocate to what matters.
Group the work that shares a goal — several teams, projects, or work types — into a program, and give it a budget. Outlay alerts before it's blown. And with the opt-in gateway in front of your calls, that budget becomes a true hard cap: an over-budget program is automatically blocked or routed down to a cheaper model — so compute flows to the programs you care about most. As priorities shift, move the budget; enforcement follows.
Illustrative. Platform is over its cap, so new Platform calls route down automatically — freeing budget for the launch. Raise a program's cap to send compute back to it.
Cost it right, plan it, take it anywhere.
Under the dashboard: cache-aware costing that doesn't overstate agentic spend 5–10×, quarter forecasting and backlog estimation, exports + a read-only API, and every integration — all reconciled to your invoice.
Cost it right
Cache-aware pricing across Anthropic, Bedrock, Vertex & OpenAI — reconciled to the invoice, so the number is real, not a token estimate.
Plan it
Forecast a quarter from open scope, and estimate planned epics from their requirements before you build — with measured accuracy on your own work.
Take it anywhere
FOCUS-aligned export, a read-only BI/warehouse API, and SIEM audit-log streaming — plus webhooks and a month-end close pack. No lock-in.
Built to pass your security review.
Most spend tools see everything you send. Outlay is built so the sensitive data physically can't reach us — purpose-built for teams that can't let prompts leave their environment: healthcare, legal, and financial services.
A different category, on purpose.
Every adjacent tool stops at the infrastructure layer — so none of them attribute AI spend to the work you plan, or budget it by scope.
Allocate the cloud bill
Cloudability, Vantage, Kubecost — great for cloud cost, but blind to which ticket or epic your AI spend belongs to.
Trace the API call
Langfuse, Helicone, Datadog LLM — they debug quality and latency, then stop at an infrastructure tag. No budget by scope.
Cap per seat
Anthropic, OpenAI, Cursor admin — per-seat limits, and token math that can price cache reads several times too high.
Where they fit: keep a FinOps suite for cloud, and observability for debugging quality. Outlay is the layer they can't be — AI spend attributed to the work you plan, forecast by scope, and held to budget. See the full comparison →
Pricing, scoped to your AI spend.
What you pay depends on your AI spend, your team, and how much you want to govern — so we set it with you. Start with a read-only pilot that maps your real spend, then we walk you through pricing scoped to it in a short consultation.
Your first weeks
A focused start: connect one tracker + your AI tools, get your real spend mapped to tickets and a budget forecast in weeks — read-only, no app rewrite.
- ✓ Spend attributed to your tickets, epics & roadmap
- ✓ Budget-vs-actual with pace-based guardrails
- ✓ A real ticket-coverage & forecast read on your data
- ✓ A team that ships the features you need, fast
- ✓ Connect one tracker + your AI tools with read-only tokens
- ✓ Spend mapped to tickets, a forecast, and a measured-accuracy read
- ✓ Prompts & keys never leave your environment
Pricing for ongoing budgeting & governance is scoped to your usage — book a pricing consultation.
Questions, answered.
How does Outlay attribute spend to a ticket?
It resolves the work context of each AI call from the most reliable signal available — an explicit task tag from your agent launcher or CI, the git branch, the PR's closing-issue link, or a commit trailer — and maps it to the ticket, epic, and roadmap in Jira/Linear/GitHub. Where a team already links work to tickets it's automatic; where they don't, a one-line explicit tag makes it reliable — even for remote/CI agents where the branch is detached.
Do you see my prompts or my customers' data?
No. Outlay connects with read-only tokens and reads metadata — task category, token counts, ticket IDs, and your provider's usage data. Prompt text, model outputs, and your API key never reach our servers.
Are the guardrails hard caps, or just alerts?
Both — your choice, per program. By default they're pace-based projections: a scope on track to exceed its budget is flagged warn (and over once it crosses), so a lead acts while there's time — Outlay never touches your traffic. For a true hard cap, set a program to enforce: with the opt-in gateway in front of your calls, an over-budget program is automatically blocked or routed down to a cheaper model. That gateway is the one mode where we're in your path, it's entirely opt-in, and it fails open — a control-plane blip never blocks your traffic, only a budget you set being exceeded.
How accurate is the forecast?
We don't ask you to trust a vendor benchmark. Outlay back-tests its forecast on your own closed tickets, leave-one-out — hide a ticket, predict it from the rest, compare to what it actually cost — and shows the measured error and the sample size, by work type. As more work closes, the number sharpens.
Can it estimate work that hasn't been built yet?
Yes — that's the forward estimator. Hand it a planned backlog (epics/tickets with their requirements, design docs, and story points) and it prices each item against the cost-per-work-type model learned from your own delivered work, returning a per-item and total estimate with a low–high confidence band. Under-specified items are flagged to tighten rather than guessed, so you can budget an epic or a sprint before committing to it.
What does it work with?
Trackers: Jira, Linear, GitHub Issues. AI tools: Claude Code, Cursor, and the Anthropic API (per-call usage + the org admin API for reconciliation). Read-only to start — no app rewrite.
How does pricing work?
Pricing is scoped to your AI spend, team size, and how much you want to govern, so we set it together. Start with a read-only pilot — it's free and maps your real spend — then we walk you through pricing in a short consultation. Book one.
Put your AI spend back on a budget.
See what your AI compute costs per ticket, epic, and team — and where it's about to go over. Start with a read-only pilot; we'll scope pricing with you.
Read-only to start · prompts never leave your environment · no app rewrite