AI Agent Pricing
Plans for designing and implementing AI agents that research, summarize, route, draft, retrieve knowledge, support decisions, update approved tools, and hand work back to humans when judgment is needed. Pricing starts at the listed amounts and may change based on workflow complexity, integrations, data access, governance, testing depth, and support requirements.
Pricing decision map
Choose by workflow complexity, not by guesswork.
Scope filter
If the workflow touches more tools, people, or decisions, the plan moves up.
Pricing logic
AI agents are different from simple chatbots. A chatbot mostly responds. An agent is designed to complete a bounded task: gather context, follow business rules, use approved tools, prepare an output, and escalate when confidence, permission, or policy runs out. The commercial value comes from reducing repeated decision work without removing human control.
Scope transparency
Listed prices are starting points. Final scope may change based on complexity, number of workflows, integrations, data access, governance, testing depth, and support needs. Software subscriptions, AI API usage, hosting, CRM tools, and third-party platform costs remain client-managed unless agreed separately. Additional work beyond approved scope is billed at $40/hour.
How we evaluate fit
Most agent projects fail when the team starts with the model instead of the job the agent should perform.
A useful AI agent needs task boundaries, trusted source context, tool permissions, approval rules, and fallback handling.
Good agents reduce repetitive thinking work while keeping human judgment, review, and ownership visible.
The right first agent is usually narrow: one workflow, one decision path, one measurable output, and one reliable handoff.
Agent scope
A lightweight assistant can summarize or retrieve information. A serious AI agent needs workflow rules, source context, permission boundaries, testing, and a human review path. That is why agent pricing is based on operational responsibility, not a generic feature count.
Research, summarize, route, qualify, draft, extract, update, or coordinate a defined workflow.
Documents, CRM records, tickets, websites, knowledge bases, forms, databases, or internal notes.
Whether the agent only prepares outputs or can use approved APIs, CRMs, forms, or workspaces.
Approval rules, confidence thresholds, escalation paths, audit notes, and human fallback behavior.
Monthly, bi-weekly, weekly, or enterprise support depending on usage and business criticality.
Possible agent solutions
The strongest first agent is usually narrow enough to test, but important enough to save real time.
Reads a customer request, asks for missing context, classifies urgency, and routes the issue.
Summarizes inquiry context, checks fit, drafts CRM notes, and prepares follow-up points.
Extracts details from files, flags missing information, and sends structured output for review.
Finds approved answers from company material and explains where the answer came from.
Plans & packages
Starts at USD $2,500/month
2-8 weeks
Design and launch one focused AI agent for a clearly defined task such as summarization, request routing, research support, document review, or internal knowledge assistance.
Ideal fit
Agent use-case discovery
Task boundary and success criteria
Prompt and instruction system
One source or workflow context
QA checklist and handoff rules
Monthly support review
Starts at USD $5,000/month
2-8 weeks
Build a multi-step AI agent that can move through a real workflow, use approved tools or data, prepare structured outputs, and route work to the right person.
Ideal fit
Agent workflow architecture
Knowledge and tool context
CRM, form, API, or workspace connection planning
Human approval and escalation logic
Testing, documentation, and enablement
Ongoing optimization cadence
Starts at USD $8,500/month
2-10 weeks
Create a connected set of agents or assistants across internal knowledge, sales support, customer support routing, documentation, operations, or reporting workflows.
Ideal fit
Multiple assistant or agent workflows
Shared knowledge structure and access logic
Governance, permissions, QA, and usage review
Integration and data-flow planning
Documentation and team training
Prioritized roadmap for additional agents
Starts at USD $14,000/month
Scoped by requirements
Design enterprise-grade AI agent systems with governance, access control, tool use, data boundaries, auditability, and support rhythm.
Ideal fit
Enterprise agent discovery
Security, permissions, and governance planning
Custom agent or assistant architecture
Tool-use and data-boundary design
Executive implementation reviews
Support and scaling roadmap
AI agent solutions
Each agent starts with one job, clear source context, approved actions, and a human fallback path. The goal is useful task execution, not uncontrolled automation.
Collect context, summarize findings, prepare briefs, and support decision prep.
Review research agents
Help teams search knowledge, draft responses, summarize documents, and find answers faster.
Review internal ai assistants
Classify requests, collect missing context, suggest next steps, and route to the right person.
Review support triage agents
Qualify inquiries, prepare CRM notes, summarize buyer context, and support follow-up.
Review sales workflow agents
Extract, classify, summarize, and route document-based work with review rules.
Review document intelligence agents
Use approved APIs, forms, CRMs, or internal systems with permission and fallback logic.
Review tool-connected agents
What is included
Process walkthroughs, tool access, sample data, user roles, and a clear implementation plan.
Chatbots, agents, automations, integrations, knowledge systems, or custom builds shipped against scope.
QA, prompt updates, fixes, documentation, review cadence, and practical improvement after launch.
Extra integrations, advanced API work, custom software, data cleanup, training, and additional scope.
Delivery roadmap
Phase 1
Review the workflow, tools, users, data, constraints, and manual work that should be reduced first.
Phase 2
Define the implementation scope, system logic, integrations, knowledge structure, and support expectations.
Phase 3
Implement the chatbot, agent, automation, integration, or custom software system with practical QA.
Phase 4
Improve prompts, data quality, routing, documentation, reliability, and user experience after launch.
Compare plans
Choose by workflow complexity, integration depth, and support cadence. Start small when one workflow is clear; move up when more teams, tools, or permissions are involved.
Swipe to compare plans
Plan 01
Starts at USD $2,500/month
Best fit
Customer conversations
Implementation depth
Conversation system
Support
Monthly to ongoing
Plan 02
Starts at USD $5,000/month
Best fit
Process handoffs
Implementation depth
Workflow system
Support
Monthly to ongoing
Plan 03
Starts at USD $8,500/month
Best fit
Task support
Implementation depth
Agent workflow
Support
Monthly to governed
Plan 04
Starts at USD $14,000/month
Best fit
Complex requirements
Implementation depth
Architecture-led
Support
Custom cadence
Questions
Short answers for the questions that usually decide whether a plan is ready to discuss.
Quick answer
You can start small. Most teams begin with one useful system, then expand once the workflow proves value.
AI agent pricing can include use-case discovery, agent workflow design, prompt and instruction systems, knowledge context, tool-use rules, integrations, QA, documentation, and post-launch support.
A chatbot mainly answers questions. An AI agent is designed to complete a bounded task such as summarizing information, routing work, preparing outputs, searching knowledge, updating tools, or handing work to a person.
Yes. Agents can be designed around CRMs, forms, APIs, documents, support tools, databases, internal workspaces, and automation platforms when access and data structure are available.
Yes. The listed AI agent prices are starting points. Final pricing may change based on workflow complexity, number of agents, integrations, data access, approval rules, security needs, testing depth, and support cadence.
Yes. The safest first step is usually one narrow agent with a clear job, source context, success criteria, and human fallback path.
Yes. Agents need prompt updates, source updates, QA, edge-case review, monitoring, and workflow tuning after launch.
Related solutions
Recommended next step
Starts at USD $5,000/month
Most serious agent work needs source context, workflow logic, testing, and a support cadence to stay reliable. Final pricing depends on tool access, integrations, governance, user roles, and support needs.