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AI agent development. Custom agents, built for production.

Requirements, architecture, tool integrations, evaluation and monitoring: custom AI agents built on Claude, connected to your systems and tested on your real cases before they go live.

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30 minutes with a solution architect.

In short

What is custom AI agent development?

Custom AI agent development means building an agent around one of your processes: its goal, the tools and data it may use, the decisions it may take and the ones it must hand to a person. Solorai builds agents on Claude, connects them to your systems through APIs and MCP, the open standard for linking AI to tools and data, and tests every release against cases from your own work.

Written and reviewed by Solorai

per workflow, with one accountable owner
1 agent
agentic security risks in the OWASP list we test against
10
for an AI agent pilot
6 to 8 weeks

What does AI agent development include?

Everything an agent needs to run in production, not just a demo.

  • Requirements

    The goal, the cases the agent must handle, the ones it must refuse and how success is measured.

  • Architecture

    Model, tools, memory, permissions and the points where a person approves, documented before the build.

  • Tool integrations

    Connections to your CRM, ERP, document stores and internal tools through APIs and MCP servers, with least-privilege access.

  • Evaluation

    A test set built from your real cases, including attempts to mislead the agent, run before every release.

  • Human approval

    Approval steps, escalation and a stop control, so people stay accountable for the decisions that matter.

  • Monitoring

    Every step logged, with quality, cost and errors tracked and alerts when results change.

How we build

From specification to production

Seven steps. An agent starts with a person approving every action and keeps approval wherever decisions matter.

  1. Specification

    Solorai with your team

    Goal, cases, data, permissions and success measures, agreed in writing.

  2. Design

    Solorai

    Architecture, tools, approval points and the test set.

  3. Build

    Solorai and technical partner

    The agent, its tools and its integrations, in a test environment.

  4. Evaluate

    Solorai with your team

    Test set, security tests and a review of the results with the process owner.

  5. Pilot

    Your team, with our support

    Real cases, with a person approving every action.

  6. Production

    Your team, with our support

    Approval kept where it matters, with monitoring and alerts on.

  7. Operate

    Solorai with your team

    A regular review of quality, cost and new cases.

Where to start

How do we start building an agent?

Fixed formats with a clear scope. Prices are agreed in a written proposal.

  • AI agents

    AI agent pilot

    One agent on one workflow, taken into production.

    Duration
    6 to 8 weeks
    Team
    With a technical partner

  • Start

    AI readiness assessment

    An analysis of your use cases and the data available for them, ending with a plan and its costs.

    Duration
    About 2 weeks

FAQ

AI agent development, in short

What is AI agent development?

Building software in which a language model plans and carries out the steps of a task with tools, such as searching a document store or updating a CRM record, within set permissions and with human approval where it matters.

Which model do you build agents on?

On Claude, Anthropic’s family of models. We choose the model by task: Opus or Sonnet for complex reasoning, Haiku for fast, high-volume steps.

How do agents connect to our systems?

Through your systems’ APIs and through MCP servers. MCP, the Model Context Protocol, is an open standard for connecting AI applications to tools and data; Anthropic donated it to the Agentic AI Foundation of the Linux Foundation in December 2025.

How do you test an AI agent before it goes live?

With a test set built from your real cases, scored on correct outcomes, correct tool use and correct escalation, plus security tests against attempts to mislead the agent. A release goes live only when it meets the agreed thresholds.

How do you stop an agent from doing something wrong?

Each agent gets only the access it needs, actions that matter wait for a person’s approval, every step is logged and a stop control halts it at once.

How much does custom AI agent development cost?

It depends on the workflow, the systems involved and the volume. Prices are agreed in a written proposal, and an AI agent pilot runs 6 to 8 weeks.

Related reading

Sources: Model Context Protocol, Regulation (EU) 2024/1689

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