Impact01
Dynamic, token-based AI billing makes standard monthly budgets obsolete.
fyscal · Autonomous finance workflow
Can finance explain where the AI budget went?
Leverage AI-native controlling agents to allocate dynamic model tokens, cloud endpoints, and infrastructure bills across teams.
The current reality
The manual AI cost tracking reality
“API model rates fluctuate. Cloud compute nodes scale dynamically. R&D sandbox keys are created. The monthly cloud invoice spikes, but finance cannot identify which project, team, or experiment drove the costs.”
Impact02
AI API keys and sandboxes lack documented corporate owners or business outcomes.
Impact03
Finance only identifies wasteful compute spikes weeks after they occurred.
Explainable by design
See the agent think in evidence, not black boxes.
A concept view of how fyscal traces discrepancies and produces reviewable reconciliation steps.
Model and Team-level AI Spend Mapping
Allocation Model (August 2026)
| Vendor / API | Logged Cost | Assigned Team | Identified Driver |
|---|---|---|---|
| OpenAI (GPT-4o) | €18,450 | Engineering (Search Product) | Batch vector indexing |
| Anthropic (Claude 3.5 Sonnet) | €12,800 | Unassigned (API Key #028) | Unknown sandbox usage |
| Amazon Web Services (SageMaker) | €44,200 | Data Science (R&D Platform) | Deep training checkpoints |
Unassigned AI Spend Flagged: €12,800
fyscal controlling agent trace: Anthropic key #028 consumed €12,800. Key origin traced to marketing sandbox test. Budget owner: Unassigned. Suggested action: Request allocation and business justification.
Structured discovery
What we cover in twenty focused minutes.
01
Map the source trail
Trace the exports, spreadsheets, and ledger files that create the manual loop.
02
Define the checks
Capture the rules, exception thresholds, and verification steps your team applies.
03
Review the agent fit
Evaluate an explainable agent workflow against your operating reality.
Zero-friction timeline
From manual gap to a clear agent map.
Share the outline
Tell us where the manual gap lives.
Book 20 minutes
Choose a focused review slot.
Leave with a map
See the evidence trail, controls, and next step.
Secure evaluation
Evaluate your workflow with fyscal
Fill out the quick questionnaire below. fyscal does not store or process live records; your setup details are strictly confidential.
Trust & control
Honest Stage & Security Boundary
fyscal is actively researching model-level cost assignment techniques. The AI cost allocation visualization is an early concept preview based on synthetic API and cloud logging metrics analyzed by autonomous agents, not a production dashboard.
Do not upload confidential agreements, active API keys, or live financial exports through any forms.: Do not upload confidential agreements, active API keys, or live financial exports through any forms.
Synthetic Data Only: Visualizations, records, and flow mapping screens operate entirely on synthetic datasets.
Human in the Loop: We believe important financial ledger events and spend reviews should remain explainable and always require deliberate human approval.
FAQ
Frequently Asked Questions
Honest answers about fyscal’s AI agents, security parameters, and co-development stage.
One workflow. Twenty minutes. Clear next steps.
Spend less time stitching systems together.
Spend more time making the decisions that matter.
Start with one real workflow. Evaluate where the manual gap sits, and explore our autonomous agent concepts over a 20-minute call.