How much are we spending?
Normalized cost, token, request, cache, and credit evidence in one workspace—without reconciling vendor tabs by hand.
Loading Pharos workspace
AI spend intelligence for operators
Navigate AI spend
with confidence.
Pharos unifies provider and gateway evidence, explains what changed, forecasts what comes next, and gives every decision a defensible trail.
Read-only reporting access · incremental sync · no model traffic in the data path
Pharos
Evidence flowingExecutive overview
Know the position. See the move.
Your real provider evidence populates this view after connection.
Spend
Provider facts
Forecast
Evidence-based
Runway
Early warning
Consumption pulse
Normalized daily movement
One ledger across the AI stack
OpenAIAnthropicOpenRouterPerplexityTogether AIFireworks AICursorAmazon Bedrock
A decision system, not another chart library
Answer the three questions that decide AI spend.
What is driving it?
Drill from provider to product, model, team, project, person, or key. Every comparison keeps its source confidence attached.
What should we do next?
See forecast risk, balance exhaustion, anomalies, and a short evidence-triggered action list. Ask Pharos to translate the numbers for any audience.
Lightweight by design
Deep on day one.
Incremental after.
Pharos performs one bounded historical backfill when you connect a provider. From then on, watermark-based syncs fetch only new or corrected evidence. The dashboard reads the normalized ledger—not vendor APIs—so navigation stays fast and provider load stays low.
Step 1
Connect read-only reporting access
Credentials are encrypted, scoped to evidence collection, and never displayed again.
Step 2
Backfill once, then sync the delta
Provider-specific windows respect documented limits; a small overlap captures late corrections.
Step 3
Normalize without erasing provenance
Cost, tokens, cache, requests, projects, people, and keys retain provider and confidence metadata.
Step 4
Reason over evidence—not guesses
Deterministic math produces the numbers. The advisor explains, compares, and proposes the next step.
One operating view
From every AI dollar to the next defensible decision.
Consumption, normalized
Compare providers and gateways, then drill into product, model, project, key, team, or person when a source supplies that dimension.
A ranked decision feed
See at most five material findings, each with its value, evidence boundary, next step, and direct path to the ledger.
Forecasts and scenarios
Review expected month end, likely range, historical accuracy, plan difference, and saved demand, price, mix, and savings scenarios.
Unit and outcome economics
Compare model cost per observed usage. Add versioned outcomes before calculating cost per ticket, run, change, or report.
Agents and workloads
Separate provider project traffic from registered workflows, then map owners, run boundaries, outcomes, and evidence.
Budgets and early warning
Track pace, burn, thresholds, forecast risk, depletion, source gaps, and alert history from normalized evidence.
Market and renewal context
Match official pricing and model-retirement records to usage. Keep provider credits, contracts, commits, and renewal deadlines distinct.
Waste without wishful math
Surface rule-backed opportunities and human-reviewed expense matches. Similar vendor names never become automatic savings claims.
Audience-ready report packs
Prepare daily, weekly, finance, board, renewal, and incident views; save immutable snapshots with scope and checksums.
Trust is part of the product
Read-only, tenant-isolated, and honest about uncertainty.
Pharos sits outside your inference path. A connector failure affects only that source; last-good evidence remains available with its successful timestamp. Credential changes and alert delivery are auditable.
Encrypted provider credentials
No plaintext keys in the database or logs
Tenant-scoped transactions
Provider failures never erase history
External news never changes ledger math
Questions
Clear answers before you connect.
Is Pharos another gateway?+
No. Pharos is an out-of-path intelligence layer. It reads supported billing and usage evidence; it does not proxy or slow model requests.
Does Pharos poll every provider on every page?+
No. Connection performs a bounded backfill. Scheduled or explicit syncs fetch incremental updates, while product pages read normalized PostgreSQL facts.
Can I use a personal account?+
Yes. Create a private workspace. Where a provider does not expose personal billing APIs, upload the provider invoice or supported usage export rather than granting unsupported access.
Are forecasts or recommendations generated by an LLM?+
The underlying arithmetic is deterministic. The advisor selects relevant experts to explain evidence, compare options, and propose follow-up actions; modeled values stay labeled.
Which sources are supported?+
OpenAI Platform, Anthropic organizations, Cursor teams, OpenRouter, and Amazon Bedrock have live connector paths. Together AI, Fireworks AI, and Perplexity use normalized provider exports where no supported account-reporting API is available.
Set a clearer course for AI spend.
Set up a private, team, or company workspace. Connect one source and let real evidence light up the experience.
Create your Pharos workspace