What does StackSpend do?
StackSpend is a cloud and AI cost monitoring platform. It connects to 13 providers — AWS, GCP, Azure, Snowflake, Vercel, ClickHouse Cloud, Elastic Cloud, OpenAI, Anthropic, Cursor, GitHub, Hugging Face, Grok (xAI), and Twilio — with read-only credentials, normalises every bill into one daily number, and categorises spend to P&L buckets. It gives you a unified dashboard and data explorer, Prophet-powered forecasting, budgets with alerts at 50/80/100%, and statistical anomaly detection. On the Business plan it traces each spike to the GitHub deploy or pull request most likely behind it. It delivers to Slack, Microsoft Teams, and email, opens assigned tickets in Linear and Jira, exposes a REST API and webhooks, and includes an in-app cost intelligence agent. Read-only, AES-256 encrypted, tenant-isolated, and GDPR compliant. Setup takes about 5 minutes with 90 days of history loaded automatically; plans start at $29/month.
Everything StackSpend does to put cloud & AI cost in your team's hands
Connect every provider, see one daily number, forecast and budget, catch the spike the day it happens — and trace it to the deploy that caused it. The whole cost loop, where your engineers already work.
13 providers · 5-minute setup · 90 days of history · read-only
One platform, the whole cost loop
StackSpend takes you from connected to in control: see the spend, understand it, forecast and budget it, catch anomalies, trace their cause, and act — without leaving Slack, Linear, or Jira.
Every provider, one normalised number
Connect AWS to Anthropic with read-only credentials and StackSpend pulls every bill into one view — normalised across cycles and currencies, categorised to P&L buckets, with 90 days of history on day one.
- ✓13 providers across cloud, AI, data, and developer tools
- ✓Read-only, AES-256 encrypted · multi-account · multi-currency
- ✓Services auto-categorised — an LLM classifies the unknowns and learns
Make it make sense
A single daily signal in Slack or email, a dashboard with traffic-light spend health, and a data explorer to drill any dimension — provider, service, tag, project, or user — then group, chart, and export exactly the slice you filtered.
- ✓Unified dashboard · MTD and projected month-end at a glance
- ✓Data explorer with drill-down, group-by, and CSV export
- ✓Tagging & auto-tag rules attribute cost to teams at ingest
Know month-end on day 9
A Prophet-powered forecast with confidence bands and a days-to-risk date, per provider and org-wide. Budgets scope to anything; auto-budgets seed the numbers from your own history; alerts land at 50, 80, and 100% before the breach, not after.
- ✓Forecast with confidence intervals and a breach date
- ✓Budgets per org, provider, project, or tag — in any currency
- ✓Auto-budgets from your historical spend
Catch the spike — and what shipped itBusiness
Statistical baselines flag the anomaly the same day. Then — the part a dashboard can't do — StackSpend links it to the GitHub deploy and pull request most likely behind it, ranked by confidence, so the engineer who shipped it sees it first.
- ✓Spike, drop, trend-change, and new-service detection with severity
- ✓Root-cause: the spike arrives attached to the deploy and PR behind it
- ✓Ranked by confidence — evidence, never asserted. You confirm.
The work lands where engineers already are
Alerts arrive in Slack, Microsoft Teams, or email. The work to fix a spike becomes a ticket in Linear or Jira — assigned to the owner, synced both ways, with the saving posted back when it resolves. Or wire it into anything with webhooks and the API.
- ✓Slack, Microsoft Teams, and email delivery
- ✓Linear & Jira: assigned tickets, two-way status, savings comment
- ✓Webhooks and a REST API for runbooks, PagerDuty, and custom flows
AI spend, tracked to the token — with an agent that explains it
AI is the fastest-growing line on the bill and the hardest to read. StackSpend tracks OpenAI, Anthropic, Cursor, Hugging Face, and Grok at the token and model level, folds it into the same P&L view as your cloud, and puts an analyst on top of it.
- ✓Token- and model-level cost across every AI provider
- ✓AI spend normalised alongside cloud, in one number
- ✓Per-team and per-product AI attribution via tags
- ✓Anomaly detection tuned to spiky, usage-based AI bills
Ask, and it answers with receipts
Plain-English questions get analyst-grade answers with cited figures. The agent chains the queries, explains the variance, and — only after you confirm — takes the action: acknowledging anomalies, creating budgets, drafting a board summary in your currency.
- ✓Multi-step analysis grounded in exact figures and dates
- ✓Every write action waits for your confirmation
- ✓Copy-ready board and P&L summaries, self-serve
Find the features that matter to you
The same platform meets each person where they sit — from the CTO accountable for burn to the engineer who shipped the change.
Engineering leader
One consolidated view, same-day anomaly alerts, a defensible forecast, and per-team attribution.
ExploreFinance partner
Costs mapped to P&L categories, budgets with thresholds, multi-currency, and board-ready summaries.
ExplorePlatform engineer
Drill any dimension in the explorer, a full REST API, tagging, and root-cause on every spike.
ExploreStartup founder
Five-minute setup, native AI-provider coverage, and auto-budgets seeded from your own history.
ExploreOps / IT lead
Audit logging, GDPR export and delete, team management, and budget guardrails across the stack.
ExploreConnects to your stack, ships where your team works
AWSGCPGitHubAzureSnowflakeVercelClickHouse CloudElastic CloudOpenAIAnthropicClaudeCursorHugging FaceGrok (xAI)Twilio
Everything included
Every capability in the platform, end to end.
Connect
Providers · scheduled sync · multi-account
Normalise
Cost data model · categorization · currency
Attribute
Tagging · auto-tag rules · group-by
Budget
Budgets · auto-budgets · 50/80/100% alerts
Detect
Anomalies · baselines · severity · z-score
Trace
Source-control correlation (Business)
Forecast
Prophet model · days-to-risk · bands
Monitor
Spend health · risk · momentum
Explore
Data explorer · drill-down · CSV export
Agent
In-app cost agent · analytics query API
Notify
Slack · Microsoft Teams · email
Dispatch
Linear · Jira · webhooks · FinOps tasks
Secure
Magic-link auth · roles · tenant isolation
Comply
GDPR export & delete · audit logging
Operate
Durable job queue · self-serve billing
Build
REST API · consistent envelopes
Feature FAQ
Does StackSpend cover both cloud infrastructure and AI/LLM providers?
Does StackSpend detect cost anomalies?
Can StackSpend tell me what caused a cost spike?
Can I attribute costs to a team, feature, product, or customer?
Does StackSpend forecast spend and enforce budgets?
Does it integrate with Slack, Microsoft Teams, Linear, and Jira?
Does StackSpend have an API, webhooks, and MCP?
How is my cost data secured?
Make cost something your engineers own — not something one person watches.
Connect providers in minutes. Get 90 days of visibility, same-day anomaly detection, and — on Business — the deploy behind every spike.