Set a defensible internal budget before the first RFP
Model the expected cost range for an AI project across agents, copilots, RAG systems, and classifiers. The calculator uses a transparent formula grounded in our 2026 pricing benchmark so you can pressure-test vendor quotes and set an internal budget with defensible numbers.
Why use it
What you'll get out of five minutes with this tool
Compare vendor proposals against a benchmark-driven estimate
Understand which scope levers move price the most
Share a repeatable estimate with non-technical stakeholders
Inputs
Describe your AI project
Every input maps directly to a documented line item in the 2026 pricing benchmark.
Multi-step, tool-using agent with planning and memory.
Complexity
Multiple flows, basic guardrails, eval harness.
Third-party APIs, data sources, or internal systems.
Engineers dedicated to this build.
Delivery stage
Your estimate
Projected budget range
Based on 500+ AI projects tracked in our 2026 pricing benchmark.
Midpoint estimate
$48,600
Likely range: $38,880 – $63,180
Estimated timeline
8 weeks
Team
2 engs
What's included
- • Discovery, architecture, and evaluation harness
- • Core build with guardrails and observability
- • Integration setup for 3 systems
- • QA, hardening, and deployment
30-minute scoping call. No slide decks. We bring our own numbers.
Questions
Frequently asked
How accurate is this AI cost calculator?
The formula is calibrated against 500+ AI projects from our 2026 pricing benchmark. Expect the midpoint to land within 15-20% of a final scoped quote for most projects.
What does the cost include?
Discovery, architecture, core build, evaluation harness, guardrails, basic observability, integration setup, QA, and deployment. Ongoing model usage and retainers are priced separately.
Does complexity really triple the cost?
Yes — agentic workflows with tool use, strong guardrails, and observability consistently came in at roughly 3x simple single-model builds in our data.
What's the difference between POC, MVP, and production?
POC is a scoped-down proof at 0.5x. MVP is launch-ready with happy-path flows and basic evals. Production is hardened, monitored, and SLA-backed at roughly 1.8x MVP cost.