AI spend governance & engineering Capitalisation

You spent $200 on AI yesterday.
On what, exactly?

EngLedger connects every AI dollar to the engineering work it supported. See which models, teams and initiatives consumed the budget, what they delivered, and where you are overspending, with evidence finance can trust.

14 days full access. No credit card required.

Integrated with
JiraBitbucketasanaGeminiDeepSeekPerplexityLocal LLMs
This period · one line worth acting on
$2,480/mo
correlational · this period
evidence
High-cost models are carrying work cheaper ones could. Estimated headroom, not a verdict: the sessions behind it are one click away.

That caveat stays on the number. EngLedger shows honest numbers: correlational labelled as correlational, unattributed shown rather than folded into a total. It leads the page because it is the line you would act on.

14 days
Full access, no credit card
30 min
Connect to first report
Multi-provider
One spend view
23.2B+
AI tokens metered
The questions your AI bill cannot answer

You have the invoices. EngLedger shows what they delivered.

🔌
Where did the AI budget go?
See every request, model and provider in one governed view. Costs from Anthropic, OpenAI and self-hosted models finally add up to one number.
🔗
What did that spend deliver?
Connect AI spend to the tickets and initiatives it supported. EngLedger shows the attributed work and leaves the unexplained remainder visible.
📉
Where are we overspending?
Find expensive models doing work cheaper ones may handle, failed-request burn, weak cache reuse and spend that is not tied to delivery, ranked by financial impact.
⚖️
Can we defend the number?
Give finance the evidence behind every figure. Correlation is labelled, estimates stay separate, and every change remains in the audit trail.
👥
Will this become employee surveillance?
No. Organisation and team views come first, individual detail is opt-in, and every person can see exactly what their organisation can see.
Stop reconciling Jira exports in spreadsheets

R&D and IP,
built from the work itself.

EngLedger turns worklogs, commits and pull requests into a classified, reconciled monthly ledger. Capitalisable and expensed work is split, checked and locked with the supporting evidence, without engineering writing another month-end explanation email.

Explore the engineering ledger →

Take the 2-minute R&D Audit Readiness check →

Monthly ledgerBalanced
Capitalised
$96,400
Expensed
$14,200
Cap rate
87.2%period locked
From first sync to period close

Connected in the morning.
Reporting by the afternoon.

01
Connect
Link Jira, GitHub, Bitbucket and Asana, and connect your AI tools. Syncing starts immediately.
02
Resolve
Accounts and AI tokens across every tool resolve to one person, so cost and effort land on the right work.
03
Classify and attribute
Rules classify tickets and commits; AI sessions attach to the tickets they touched. Everything is overridable, and everything is logged.
04
Report and close
Readouts, exceptions, exports, period lock. Finance self-serves; engineering stops writing explanation emails.
Integrations3 connected
Jira
Jira
● synced 4m ago
GitHub
GitHub
● synced 12m ago
Asana
Asana
● synced 26m ago
Azure DevOps
Azure DevOps
not connected
AI metering
AI
All providers
● 49,832 requests metered this period
Classification rules
type = Story→ Cap
type = Feature→ Cap
type = Bug→ Non-cap
label = support→ Non-cap
“Stop reconciling Jira exports in Excel. Move from manual guesswork to automated, audit-ready precision that stands up to any scrutiny.”
14 days
Saved per quarter on audit prep
100%
Audit queries answered on first request
3 teams
Engineering, Finance, and Legal now aligned
4h
From sign-up to first complete report
Integrations

Works with the tools your team already uses

Connect Jira, GitHub, Bitbucket and Asana, meter every AI provider (Anthropic, OpenAI and any OpenAI-compatible endpoint) and add more from a growing list. No new workflows, no process changes.

See all integrations →

Security & Privacy

Your IP stays yours.
We only track the metadata.

Read-only scoped access to your work tools. We never store your source code: commit syncs record file paths and line counts, never the code itself. An append-only audit trail sits under every number, and each organisation's data is isolated at the row level.

When AI prompts pass through metering, work intent is classified in-boundary on a self-hosted model, and captured content is held on a configurable retention clock, then redacted: the metadata stays, the prompt text does not. Reporting leads with team-level views, and each engineer sees exactly what their organisation sees.

Read about security & privacy →

Data access boundariesRead-only
Ticket Metadata→ Allowed
Commit Timestamps→ Allowed
Source Code Body→ Blocked
Ticket Descriptions/PII→ Blocked
Get started today

Know what your AI spend delivered. By this afternoon.

Connect your tools and read your first AI spend readout today.

14-day trial. No credit card. Setup in minutes, not weeks.

Not sure your claim would hold up? Take the 2-minute R&D Audit Readiness check →