Interactive Tool

AI Agent Total Cost of Ownership Calculator

Model the real cost of moving agentic AI from proof-of-concept into production: build labor, data readiness, orchestration, inference growth, observability, and human-in-the-loop governance.

Start Modeling

Initial Implementation

Architecture and engineering hours Blended hourly rate Data preparation volume (GB) Data pipeline cost per GB Infrastructure setup Security and compliance review Change management and training Tool/schema integration budget

Usage and Inference

Model pricing tier Daily agent tasks Avg input tokens per task Avg output tokens per task Input cost per 1M tokens Cached input cost per 1M tokens Output cost per 1M tokens Agent reasoning multiplier Annual usage growth (%) Token safety buffer (%) Prompt cache hit rate (%) Tool/search calls per task Tool/search cost per 1K calls

Recurring Operations

Orchestration hosting / month Vector database and storage / month Observability and eval tools / month Governance FTE in Year 1 Fully loaded annual FTE cost Governance reduction per year (%) Fine-tuning and prompt ops / month Support, QA, incident response / month

Total 3-Year TCO $0

Adjust the model to see the cost profile.

Initial build $0

3-year operations $0

Year 1 monthly run-rate $0

Effective cost per task $0

Year	Model + Tools	Platform	Governance	Total

What This Includes

The expensive part is the production system around the agent.

Build Costs

Architecture, prompt and tool design, RAG pipelines, cloud setup, security review, red-teaming, and end-user change management.

Run Costs

LLM inference, prompt-cache savings, tool/search calls, stateful orchestration, vector database reads/writes, tracing, evals, support, and recurring model or prompt improvements.

Governance

Human review for edge cases, high-risk actions, approvals, incident triage, hallucination correction, and audit trails.