UBIKON.ioAI
AI Agent Development
Typical engagement: $18k–$70k · 6–16 weeks
What this is
Ubikon builds production AI agent systems — multi-step workflows where Claude plans, calls tools, and checks its own work, using MCP for a standard tool-use interface rather than bespoke integrations per tool. A typical agent engagement runs $18k–$70k across 6–16 weeks, priced by how many systems the agent needs to touch and how much autonomy it is given.
What you get
Concrete deliverables, not a vague promise.
- —A defined tool set with explicit permissions — the agent can only do what you've actually authorized
- —An evaluation harness testing the agent against real multi-step scenarios, not single-turn prompts
- —Human-in-the-loop checkpoints on any action with real-world consequences (payments, sends, deletes)
- —Full observability: every tool call, decision and retry logged and reviewable
- —Rate limiting and cost ceilings so a stuck agent loop can't run away
How we build it
Stack and architecture for a typical build.
Claude API with MCP for tool use, a task queue for long-running multi-step workflows, and structured logging so every agent decision is auditable after the fact — not just the final output.
Pricing
Where the number comes from.
The $18k–$70k range above is priced from real delivery data across 300+ completed projects — not a day rate multiplied by a guess. A full itemized breakdown by phase is available on a scoping call, or get a rough one now from the calculator below.
Open the cost calculator →The honest comparison
Agent automation vs a fixed workflow / rule engine
Agents are the right tool when the steps genuinely vary; a fixed workflow is cheaper and safer when they don't.
| AI agent | Fixed workflow / rules engine | |
|---|---|---|
| Handles novel input variation | Yes, by design | Only what was explicitly coded for |
| Predictability | Bounded by eval + guardrails | Fully deterministic |
| Build cost | Higher — needs evaluation + guardrails | Lower, faster to ship |
| Best fit | Research, multi-system coordination, judgment-heavy tasks | High-volume, low-variation, compliance-sensitive processes |
Process
6–16 weeks, start to launch.
Workflow mapping
The real steps a human currently takes, mapped before any code is written.
Fixed quote, 48 hours
Priced by tool count and required autonomy level.
Build with guardrails first
Permissions and human checkpoints are designed before the agent logic, not bolted on after.
Launch with full observability
Every decision logged and reviewable from day one in production.
Straight answers
What buyers ask about this service
What is the difference between an AI agent and a chatbot? +
A chatbot answers questions in a single turn. An agent plans across multiple steps, calls real tools (APIs, databases, other systems), checks its own work, and can retry or escalate — it takes actions, not just generates text.
How do you prevent an agent from doing something wrong? +
Explicit tool permissions (the agent can only call what it is authorized to call), human-in-the-loop checkpoints on any consequential action, and a full audit log of every decision — reviewed against a real evaluation harness before launch.
What is MCP and why does it matter? +
Model Context Protocol is a standard interface for connecting an AI model to tools and data sources. It means each new tool integration follows one consistent pattern instead of a bespoke integration per tool, which matters for both build speed and long-term maintainability.
How much does an AI agent system cost? +
Typically $18,000–$70,000, priced primarily by how many distinct tools/systems the agent needs to coordinate and how much autonomy it is given — a single-tool agent with human approval on every action costs meaningfully less than a multi-system autonomous workflow.
Related
Other services worth a look
One call. One fixed number.
Tell us about your ai agent development project.
30 minutes, no deck. A fixed quote follows within 48 hours.