AI Cost Analytics
Know what your AI features really cost
Per customer, per feature, per model — without storing prompts or changing your AI stack.
Track usage and cost, not prompts. B2B SaaS teams use SaaS Tracker to see AI economics before renewal conversations and pricing decisions.
When AI ships, finance and product need the same picture
- • “We don’t know what AI costs per customer or per feature.”
- • Trial or small accounts consume a disproportionate share of tokens.
- • Pricing and packaging don’t reflect AI margin.
- • Teams want AI cost + MRR in one place — not another spreadsheet.
Your app stays in control — we only see events
Integration is event-based on the same Ingest API as the rest of SaaS Tracker. Your code calls OpenAI, Anthropic, Azure, or others as today, then sends metadata after each call.
- ✓ No AI gateway or proxy in the path
- ✓ No prompt or response storage
- ✓ Dashboards in Analytics → AI Cost
Data flow
- 1 Your app calls the provider API
- 2 Provider returns tokens + metadata
- 3 Send event data to SaaS Tracker Include your cost in the event, or model + tokens for us to price
- 4 View AI Cost dashboards per customer, feature, and model
Two ways to record cost
Use whichever fits your stack — you can rely on one approach or combine them as your integration matures.
Send cost in the event
Include the cost for each AI call in your event data — for example what your provider charged or what you already calculated in application code. SaaS Tracker aggregates spend by customer organization, feature, and model.
Best when you already have authoritative per-call cost from the provider or your own billing logic.
Send model + tokens — we calculate price
Send provider, model, and token counts only. SaaS Tracker applies EUR pricing at ingest from the global model catalog and any negotiated rates you configure in Settings — we track pricing so you do not have to maintain rate tables in code.
Best when you want consistent, catalog-based costing without duplicating provider price lists in your app.
What you see in the product
Analytics → AI Cost — overview, customers, features, value signals, and recent calls.
Overview
AI cost over time, KPIs (cost, calls, avg per org), and top features and models.
Customers
Spend per customer organization, MRR context, billing status, and margin-risk signals.
Features
Cost by feature name — e.g. support_reply_generator — so product teams see what drives spend.
Value signals
Growth plan and above: accepted, rejected, and edited outputs; cost per accepted result.
Recent calls
Call explorer with filters and metadata. No message content — privacy by design.
Screenshot coming soon: sign in at app.saastracker.eu → Analytics → AI Cost → Overview.
Built for B2B SaaS economics
Privacy by design
Metadata and tokens only — never prompts or model responses.
No infrastructure change
Call providers directly, then send an event. No gateway, no proxy.
Your cost or ours
Send cost in the event and we roll it up — or send provider, model, and tokens and we calculate EUR cost from tracked pricing.
Same platform as org health
AI spend links to customer_org_id and imported MRR on one account-level timeline.
Integration in one pipeline
Send events through the Ingest API after each AI interaction. On each completed call, either pass through the cost you already know or pass provider, model, and token counts and let SaaS Tracker derive EUR cost from tracked pricing.
Always include customer_org_id, properties.feature, and ai_call_id where relevant for output events. See the docs for exact property names per mode.
- ai_call_completed
- ai_call_failed
- ai_output_accepted
- ai_output_rejected
- ai_output_edited
Details: AI Cost Analytics docs · Event schema
Guides on AI cost per customer
Practical reads on attribution, margin, and metadata-only tracking — without storing prompts.
What Is AI Cost Analytics for SaaS?
AI cost analytics helps SaaS teams track AI feature costs by customer, feature, model, and plan — and connect usage to value, margin, and retention.
Read article →How to Track AI Costs per Customer in B2B SaaS
Learn how B2B SaaS teams can track AI costs per customer, connect LLM spend to MRR, and see which accounts, features, and models affect margin.
Read article →AI Cost Analytics Without Storing Prompts
Learn how SaaS teams can track AI usage, tokens, models, features, and customer-level cost using metadata only — without storing prompts or responses.
Read article →Why Your OpenAI Bill Does Not Tell You Which Customers Are Profitable
Provider invoices show total model cost, but not feature value or revenue per account. Learn how to connect OpenAI spend to SaaS AI unit economics at the organization level.
Read article →From €49/month — AI economics first
The AI Cost plan is a focused entry SKU: AI Cost Analytics and ingest — without the full product analytics package. Upgrade to Starter when you need timelines, org health, and revenue signals.
Common questions
- Can I send cost myself, or do you calculate it?
- Both. Send cost in the event and we aggregate it, or send provider, model, and tokens and we calculate EUR cost at ingest from our pricing catalog and your Settings overrides.
- Do you store prompts or chat content?
- No — metadata and token counts only.
- Is there an AI gateway in the product?
- No. Your application keeps calling providers; you send events afterward.
- Are AI cost alerts included?
- Not yet — alerting is on the roadmap, not part of the current release.
- What happens when I change model pricing?
- New events use updated catalog or negotiated rates. Historical rows are not automatically recalculated when aliases or prices change.
Ready to see AI cost per customer?
14-day trial · no credit card · AI Cost Analytics included on trial