AI spend, usage, and ROI intelligence

See. Understand. Act.

Pharos Agent brings AI spend, usage, and ROI intelligence into one clear view. Compare providers and models, see where the month, quarter, or year is heading, optimize your AI bill, and act on the opportunities that matter.

Measure token economics, connect AI costs to business outcomes, and get deeper analytics on your spend and usage against industry, geography, and growth-stage peers.

For solo builders, teams, and companies. Free for solo builders.

Connect your first account View demo workspace Open your workspace

Normalized on FOCUS: the FinOps Open Cost and Usage Specification · read-only reporting · incremental sync · no model traffic in the data path

Unit costs fall. The bill still grows.

Twelve months of AI spend across every category Pharos covers. Sample figures, not a customer workspace.

Model APIs
AI seats
Infrastructure
Shadow AI

Usage, 12 months

16.5B → 109B tokens6.6×

Unit cost per 1M tokens

$1.61 → $0.88−45%

Spend

$61.2K → $158.9K2.6×

Sample figures · unit cost falls, but volume rises faster

Supported AI stack

Every provider you pay, in one place.

Learn more

AI applications & seats

4 sources

Cursor
Replit
Emergent
GitHub Copilot

Model APIs

10 sources

OpenAI
Anthropic
Google Gemini
Perplexity
Mistral AI
Cohere
Groq
DeepSeek
xAI
ElevenLabs

Gateways & inference

8 sources

OpenRouter
Ramp Router
Together AI
Fireworks AI
Anyscale
Baseten
Modal
Fal.ai

Cloud & data platforms

5 sources

Amazon Bedrock
Azure OpenAI
Google Vertex AI
Snowflake
Databricks

Built for every owner of the AI bill.

Solo builders get clarity. Teams assign ownership. Companies govern spend.

Solo builders

See personal API spend, forecast the month, and get warned before you cross your limit. Free, with no credit card or expiring trial.

Start free

Teams

Assign keys and projects, set shared budgets, and give every owner the same view of spend.

Talk to us about a team workspace

Companies

Give finance, engineering, and procurement one governed record of cost, usage, ownership, and invoices.

Talk to us about a company workspace

Why it breaks

AI spend changes before the invoice arrives.

Usage moves daily, ownership is fragmented, and finance sees the problem last.

Usage moves every day

Token, request, and seat charges change continuously. Static software budgets do not.

Ownership fragments

Engineering chooses the tools. Finance receives the bill. Procurement sees neither until renewal.

The invoice arrives too late

By month close, the opportunity to correct routing, usage, or budget drift is gone.

How it works

From provider data to decisions you can defend.

The Pharos overview: August is forecast $793.16 above the approved plan, with the figures behind that claim and the highest-confidence next step. — See the gap. Know the first move.
The executive view pairs the forecast, plan, and highest-confidence action.

Connect

Bring cost and usage into one ledger.

Use read-only APIs where providers support them. Add invoices or exports for the rest.

27 sources
FOCUS-aligned cost and usage
Daily incremental sync

Explain

Separate volume, price, and model mix.

See what changed, what caused it, and how unit economics moved.

Price, volume, and mix
Cost per outcome
Unusual-day detection

Control

Set limits before spend drifts.

Forecast against budgets and route alerts by email or Slack.

Scoped budgets and alerts
Forecast with an 80% range
Renewal and commitment dates

Prove

Show the source behind every figure.

Keep provider, invoice, and estimated values distinct from dashboard to export.

Invoice matched, provider reported, Pharos estimate
Checked against your invoice
CSV, PDF, and Markdown export

Where it lands

A forecast you can check against what already happened.

Pharos scores every forecast against the month that followed. The dashed line behind the divider is what it predicted, so the misses sit on the chart instead of in a footnote.

Each miss corrects the next forecast. The model follows your spending as it moves, rather than a curve someone fitted once.

The range comes from how wrong the model has recently been. It tightens as the model improves, and it never claims a precision the record does not support.

Aug '26 closed at $158.9K. Nov '26 is forecast at $191.7K.

The dashed line is what Pharos forecast a month ahead, at every month. The hairlines are how far off it was. Sample figures, not a customer workspace.

Actual · invoice matched
Forecast · Pharos estimate
Approved plan

Last closed month · Aug '26

$158.9K

Invoice matched

Forecast · Nov '26

$191.7K+$26.7K vs plan

Pharos estimate

Average miss · last 5 months

3.3%from 6.5%

Pharos estimate

80% range · Nov '26

$177.9K to $205.5K

Pharos estimate

Plan $165.0K/mo · the forecast passes it in Sep '26 · sample figures

The agent

Ask in a sentence. Check every number in the answer.

Ask why costs changed, where the current period is heading, or what to do next. Pharos selects the specialist best suited to the question, from planning and unit economics to invoice review and governance.

Answers use your current workspace data and name the source records behind every figure. Suggested questions adapt to the information you have connected.

The agent reads FOCUS-aligned cost and usage first, then adoption and business-value records where they exist. FOCUS standardizes the first layer; Pharos supplies the context needed for adoption and ROI analysis.

Code calculates every figure. Ask Pharos explains those results, compares options, and points to the records used in the answer. It never computes a number itself.

Six specialists route each question to an operating advisor, planner, unit-economics and routing expert, invoice explainer, incident investigator, or governance advisor.

Nine specialist tools, with arithmetic handled in code: The tools cover spend, trends, efficiency, changes, usage, recommendations, invoices, and connection health. The model chooses the right tools and explains the results; code calculates every figure.
Every tool call stays with the answer: Pharos records each tool, its inputs, and its result. Open the record behind any sentence you want to check.
A separate review checks the answer: A second model compares the answer with its tool results and flags anything that does not match.
Every figure keeps its source label: Agent answers use the same labels as the rest of Pharos. A figure without supporting data is not shown, and an estimate always remains an estimate.

Ask Pharos answering a question about spend, with the figures it read and the records behind them named in the reply. — Every figure in the answer was computed by code.
The agent reads the ledger and cites it. It never does the arithmetic on a number you are shown.

Evidence

Every number shows its source.

Provider reported, invoice matched, or clearly labeled as a Pharos estimate.

Invoice matched: Matched to the provider invoice for the period.
Provider reported: Read from the provider billing or usage API.
Pharos estimate: Calculated by a visible rule and labeled wherever it appears.

Code does the math. No language model computes a figure you are shown. The agent only explains numbers that code already produced.

Missing data shows a dash. A dash means Pharos has no measurement for that value. It never means zero.

The Pharos sources register: three provider connections, 67.2% of spend matched to an invoice, one named data gap, and what each source reports with its last refresh and evidence state. — Coverage, freshness, and gaps in one register.
Each connection shows what it reports, when it refreshed, and what remains missing.

Inside the workspace

Inside your Pharos workspace.

Spend, in one place

Every provider and gateway in one total. Open any model, project, key, team, or person the source reports.

Ranked findings

Five at a time, at most. Each one says what it is worth in dollars and shows the records behind it.

Forecasts and scenarios

Where the month lands, with an 80% range and how wrong past forecasts were. Save a scenario to test a change before you commit to it.

Unit and outcome economics

Cost per million tokens, and cost per outcome you register: a resolved ticket, a merged change, a report produced.

Agents and workloads

Agent traffic looks like ordinary API spend until you split it out. Register a workflow and you get its runs, owners, and outcomes separately.

Market and renewal context

List prices and model retirement dates, matched to what you run. So do your credits, commitments and renewal dates.

Savings you can check

Every savings figure traces back to a rule you can read on the page.

Report packs

A daily brief, a board pack, an incident review. Each one saves as a snapshot nobody can edit, and exports to CSV, PDF, or Markdown.

Know what changed, what it bought, and what to do next.

Move from topline spend to unit economics, peer context, and business outcomes.

Why did cost change?

Separate volume, price, and model mix.

Pharos reconciles the drivers to the total change.

Are we efficient for our peers?

Compare within your industry, size, and stage.

Pharos publishes private cohort percentiles once at least 10 companies qualify.

What did the spend produce?

Measure cost per outcome.

Connect AI spend to resolved tickets, merged changes, agent runs, or another business result.

Can leadership trust it?

Every figure carries a source label.

Provider-reported, invoice-matched, and estimated values remain distinct.

Unit economics in Pharos: blended cost per million tokens beside cost per support case and per agent run, with volume, price and model-mix effects decomposed. — Move from cost per token to cost per outcome.
Track the blended rate beside cost per case, agent run, or business result.

Counted from each vendor’s own integrations and product pages in August 2026. Four rows below go to a competitor, and one Pharos loses outright.

Direct AI connectors

Pharos: 25 · OpenAI, Anthropic, Google Gemini, Cursor, Replit, Emergent +19 more
Vantage: 7 · Anthropic, Anyscale, Baseten, Cursor, ElevenLabs, Modal, OpenAI
Finout: 6 · Anthropic, OpenAI, OpenAI Codex, fal.ai, GitHub, Cursor
Amnic: 6 · OpenAI, Anthropic, xAI Grok, Google Gemini, Mistral AI, Amazon Bedrock
Ramp: 4 · OpenAI, Anthropic, Google Gemini, Cursor
1Password: 3 · Cursor, Anthropic (Claude), OpenAI

Gateways and routers

Pharos: OpenRouter, Together, Fireworks, Perplexity
Vantage: No
Finout: No
Amnic: No
Ramp: No
1Password: No

Whole cloud bill, built in

Pharos: FOCUS import
Vantage: AWS, Azure, GCP and more
Finout: AWS, GCP, Azure, Oracle
Amnic: AWS, Azure, GCP, Oracle
Ramp: No
1Password: No

Kubernetes and self-hosted GPU

Pharos: No
Vantage: Cluster agent
Finout: Kubernetes
Amnic: Rightsizing to the core
Ramp: No
1Password: No

Tag rules that merge messy labels

Pharos: Virtual tags, 4 operators
Vantage: Not stated
Finout: Virtual tags
Amnic: Virtual tags
Ramp: Not stated
1Password: Not stated

Every figure says where it came from

Pharos: Three labels, always shown
Vantage: Not stated
Finout: Not stated
Amnic: Not stated
Ramp: Not stated
1Password: Not stated

How you compare to similar companies

Pharos: Percentiles at 10 companies
Vantage: No
Finout: No
Amnic: No
Ramp: Index across its customers
1Password: No

Agent you can ask in plain language

Pharos: One advisor over nine tools
Vantage: MCP server for ChatGPT and Claude
Finout: Billy, plus three agents
Amnic: Four named agents
Ramp: Ramp Intelligence
1Password: Not stated

Where the agent's numbers come from

Pharos: Figures calculated in code, with every call logged
Vantage: Not stated
Finout: Not stated
Amnic: Not stated
Ramp: Not stated
1Password: Not stated

Cost per outcome you define

Pharos: Ticket, run, merged change
Vantage: No
Finout: No
Amnic: No
Ramp: No
1Password: No

Capability comparison between Pharos, Vantage, Finout, Amnic, Ramp and 1Password
Capability	Pharos	Vantage	Finout	Amnic	Ramp	1Password
Direct AI connectors	25 · OpenAI, Anthropic, Google Gemini, Cursor, Replit, Emergent +19 more	7 · Anthropic, Anyscale, Baseten, Cursor, ElevenLabs, Modal, OpenAI	6 · Anthropic, OpenAI, OpenAI Codex, fal.ai, GitHub, Cursor	6 · OpenAI, Anthropic, xAI Grok, Google Gemini, Mistral AI, Amazon Bedrock	4 · OpenAI, Anthropic, Google Gemini, Cursor	3 · Cursor, Anthropic (Claude), OpenAI
Gateways and routers	OpenRouter, Together, Fireworks, Perplexity	No	No	No	No	No
Whole cloud bill, built in	FOCUS import	AWS, Azure, GCP and more	AWS, GCP, Azure, Oracle	AWS, Azure, GCP, Oracle	No	No
Kubernetes and self-hosted GPU	No	Cluster agent	Kubernetes	Rightsizing to the core	No	No
Tag rules that merge messy labels	Virtual tags, 4 operators	Not stated	Virtual tags	Virtual tags	Not stated	Not stated
Every figure says where it came from	Three labels, always shown	Not stated	Not stated	Not stated	Not stated	Not stated
How you compare to similar companies	Percentiles at 10 companies	No	No	No	Index across its customers	No
Agent you can ask in plain language	One advisor over nine tools	MCP server for ChatGPT and Claude	Billy, plus three agents	Four named agents	Ramp Intelligence	Not stated
Where the agent's numbers come from	Figures calculated in code, with every call logged	Not stated	Not stated	Not stated	Not stated	Not stated
Cost per outcome you define	Ticket, run, merged change	No	No	No	No	No

Competitor entries repeat what each vendor publishes, and we have not verified them. “Not stated” means that vendor makes no claim on the page we cite, which is not the same as a no.

If your AI spend is one line inside a bigger cloud bill, or the money goes to GPUs you host yourself, one of the tools above fits you better. Pharos names the source of every figure and tells you where you sit against companies your size. No vendor above claims either.

Learn more

Questions

Answers before you connect anything.

What is FOCUS, and what does Pharos add?

FOCUS is an open, vendor-neutral FinOps standard for cost and usage data. Pharos uses it to normalize AI consumption and spend, then adds adoption and business-value evidence for ROI analysis. FOCUS itself does not define adoption or ROI.

What is AI spend management?

AI spend management brings model APIs, AI seat licenses, and infrastructure costs into one view. Pharos forecasts spend against your budget, calculates unit costs, and tracks what each change saved. Every figure links to its source data.

Do we have to change how we pay providers?

No. Pharos reads provider billing and usage APIs directly. Your cards, bank accounts, and accounting system stay exactly as they are.

Is Pharos another gateway?

No. Pharos reads billing and usage records, and sits outside the request path. It cannot slow a model call down.

Where do the peer benchmarks come from?

From other Pharos workspaces in your industry and size band, one vote per company, shown as percentiles. Pharos publishes a group once 10 companies match your profile. Below that, a percentile would really be one company's number, so nothing is published. Until your group forms, Pharos compares you against your own history and cites published market figures with their sources.

Are forecasts or recommendations generated by an LLM?

No. Code computes every figure. Ask Pharos uses the relevant experts to explain your records, compare options, and recommend next steps. Forecasted values are labeled Pharos estimate.

Does Pharos poll every provider on every page?

No. Connecting backfills your history once. After that, syncs run on a schedule or when you ask for one, and the pages read what is already stored.

Can I use a personal account?

Yes. Create a private workspace. If a provider has no personal billing API, upload its invoice or usage export instead.

Which sources are supported?

Pharos supports 27 sources across AI applications, model APIs, gateways, and cloud platforms. 12 sync through read-only reporting APIs; every source also accepts invoices or compatible usage exports. The Connectors page shows the exact reporting method and evidence available for each one.

Start with one provider and a single month.

Connect read-only reporting access, or upload an invoice. One month of data usually answers the question that sent you here.

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