Custom AI agent development for teams that need automation tied to your software stack and approval paths.
We build agents that can call the right context, use tools and APIs, escalate to humans, and run within cost and quality boundaries. That means orchestration, evaluation, and operational monitoring — not a single long prompt. The work sits next to your web and custom software, so the agent is part of a system people can run and support.
This page sits inside our broader ai and machine learning service cluster and is designed for teams searching with clear commercial intent.
Who this is for
- SaaS teams adding copilots or in-app AI assistants to existing products
- Operations and support leaders automating high-volume, structured workflows
- IT groups piloting internal assistants that must respect permissions and audit needs
- Leaders who want a partner that can also deliver the non-AI product engineering around the agent
Service Scope
What we typically deliver
- Use-case scoping, tool and API design, and context retrieval (including RAG where appropriate)
- Agent routing, handoffs, guardrails, and error handling in production
- Integration with auth, business rules, and existing line-of-business applications
- Evaluations, cost controls, and iteration from real user traces after launch
Delivery Process
How we move from scope to launch
Qualify the workflow
We confirm what success means, which steps require human review, and what can never be automated for compliance or quality reasons.
Design the agent and tool surface
We define the tools, data sources, and system prompts, with tests that reflect real user language and edge cases.
Implement in your environment
We build the service, connect monitoring, and align deployment with your security and infrastructure practices.
Measure and harden
We tune for accuracy, cost, and latency in production, and we extend capabilities only when the measurement supports it.
Continue exploring
Portfolio, related services, and ways to connect
AI work grounded in product engineering
Our AI company page shows how we couple LLM work with the surrounding software, APIs, and UX you need for a deployable system.
Read AI company capabilitiesA regulated domain where mistakes are expensive
The SoftServe360 case study highlights multi-tenant B2B expectations — a useful parallel when you need agents to honor strict rules and auditability.
Read the B2B platform case studyMVP to scale when the agent is the product thesis
If the agent is your wedge for a v1, our MVP program links discovery to a shippable surface.
MVP product deliveryFrequently asked questions
A custom agent is designed for specific workflows, tools, and data access in your product or operations. It includes routing, error handling, and evaluation so behavior is more predictable in production than an open-ended chat on public pages.
We use narrow scoping, retrieval, structured outputs, human-in-the-loop steps where needed, and test suites for critical paths. The goal is reliability in your domain, not a demo that only works in the meeting room.
We integrate with common model providers, vector stores, and your internal APIs, depending on hosting and data residency. The integration plan is set during discovery, not assumed.
Explore the related service cluster
Have a use case for an internal or customer-facing agent, not a slide about “agents in general?”
Describe the workflow, systems involved, and how you will judge success. We can recommend a small pilot and what must be in scope for a safe first release.
Start the conversation