Start with the bill
Connect OpenAI reporting or import Anthropic Cost and Usage reports. See spend by model, project, workspace, and API key before adding runtime telemetry.
AI cost tools compared
More than another chart of your AI bill.
Provider dashboards show what you spent. Observability tools show what happened. SpendLens AI helps you find what is driving the bill, what to optimize, and what to test safely.
What makes SpendLens AI different
From provider bill to a safer savings decision.
Find what to optimize
SpendLens AI looks beyond cost charts to surface model rightsizing, cache, batch, ownership, and usage opportunities supported by the data available.
Validate before you switch
Add lightweight, no-proxy telemetry only when you need application context. Compare quality and projected savings before changing a production model.
Alternatives and comparisons
Choose the tool that matches the job.
These products solve different problems. Here is the simplest way to understand where SpendLens AI fits.
Provider reporting
OpenAI and Anthropic dashboards
Best for: Checking provider totals and native usage
The natural place to confirm what the provider billed. They are useful for native account reporting, but may not connect spend to the application decision that created it.
Why teams consider SpendLens AI
- Combines supported provider data into one financial view
- Maps projects, workspaces, and API keys to owners
- Surfaces cost optimization opportunities, not only usage totals
- Adds workload evidence when provider reporting is not enough
LLM observability
Langfuse and LangSmith
Best for: Tracing, debugging, evaluations, and prompt development
Strong choices for teams whose main problem is understanding application behavior and output quality. Their broader developer workflows may be more than a finance-led cost review needs.
Why teams consider SpendLens AI
- Starts with provider billing data and no SDK requirement
- Keeps AI cost optimization as the primary workflow
- Ranks model and usage opportunities by financial impact
- Uses optional telemetry for deeper validation
Proxy and gateway
Helicone and AI gateways
Best for: Routing, logging, caching, and controlling requests
A gateway can centralize AI traffic and apply controls in the request path. That is valuable when routing is the goal, but it changes how requests reach the model provider.
Why teams consider SpendLens AI
- Does not proxy OpenAI or Anthropic requests
- Adds no gateway dependency or request-path latency
- Connects billing data before asking for code changes
- Helps test model savings without replacing provider clients
Cloud FinOps
CloudZero and cloud FinOps platforms
Best for: Allocating and optimizing broad infrastructure spend
Excellent when AWS, Azure, GCP, Kubernetes, and shared cloud costs are the main scope. AI API economics often need model, token, cache, and workload context that general cloud billing does not contain.
Why teams consider SpendLens AI
- Purpose-built for OpenAI and Anthropic costs
- Treats model rightsizing like EC2 rightsizing for AI
- Understands tokens, model pricing, cache, and batch signals
- Connects provider spend to engineering action
Product capabilities and packaging change over time. Evaluate each product against your current technical, security, and commercial requirements. Third-party names are used only for comparison and do not imply endorsement.
The simple difference
Think EC2 rightsizing, but for AI models.
Use provider data to find where spend needs attention. Add runtime context only where needed. Test whether a more cost-efficient model can preserve quality before switching.
STEP 1
Connect
Bring in supported provider costs
STEP 2
Find
See where savings may exist
STEP 3
Validate
Test quality before changing
Common questions
Finding the right fit.
Is SpendLens AI an observability platform?+
SpendLens AI is focused on AI cost optimization. It provides financial visibility first, then optional no-proxy runtime telemetry when a team needs workload-level evidence to validate savings.
Does SpendLens AI replace OpenAI or Anthropic dashboards?+
No. Provider dashboards remain the source for native account reporting. SpendLens AI turns supported provider data into ownership, prioritization, and optimization views.
Does SpendLens AI route or proxy AI requests?+
No. Your OpenAI and Anthropic calls continue directly to the provider. Runtime telemetry is added after calls complete.
Can SpendLens AI work alongside another observability tool?+
Yes. You can use SpendLens AI for cost analysis and savings validation while keeping an existing tracing, evaluation, or monitoring tool.
Which option should I choose?+
Choose a provider dashboard for basic totals, an observability tool for debugging and evaluations, a gateway for request routing, and SpendLens AI when the main question is what is driving the AI bill and what can be optimized safely.
Stop guessing what to cut from your AI bill.
Connect supported provider data, find where spend needs attention, and validate savings before changing your app.
Analyze my AI spend