Custom Agents
Quality at every stage. Resilience in every release. Flawless experiences every time.
When does an enterprise need a custom agent?
Some workflows are too specific for anything off the shelf. The rules may come from your own regulator, or the decision may rest with a few analysts working in a system that no product connects to.
A custom agent is an AI agent engineered end to end for one workflow or system. QKTech designs it with the business, builds it, evaluates it and runs it in production.
Services
What does a custom agent build include?
Five parts of the work decide whether an agent survives production. Each is scoped with your team before the build starts.
Design around the workflow
Agents modeled on a vendor demo tend to break on the exceptions in your real process. We map the workflow with the people who run it, decide which steps the agent owns and write the rules for handing the rest to a person.
Connection to your systems
The data an agent needs often lives in legacy systems, and the agent needs safe access to them. We connect the agent to your data, tools and legacy platforms, and we scope each permission to its task.
Multi-agent coordination
When several agents share one process, the handoffs are where failures start. Our method tests each agent’s accuracy, the context that survives each handoff and the business outcome of the whole system, then keeps checking for drift.
Security and control
An agent with tool access can act on a manipulated instruction. We test every input the agent accepts for prompt injection and data leakage, limit it to the tools it needs and keep an approval step for actions with side effects.
Handover to your team
The goal is an agent your own people can run. We document the decisions, train your engineers and hand over the specification, the evaluation suite and the roadmap.
Quantifiable proof points
What custom agents delivered in production
80%
fewer mis-tagged calls after an electric mobility company moved call summarization to a production agent, which also saved 100,000+ agent hours each year
80%
faster reporting turnaround for a consumer goods company’s field sales teams, using a conversational Data Analyst Agent
Insights
FAQs
Common questions about custom agents
These answers cover what business owners and architects ask us first.
When do we need a custom agent?
When the workflow is unique to you or no product covers it. If it is common to many companies, a pre-packaged agent is faster to deploy when one fits.
Can a custom agent work with our legacy systems?
Yes. We connect the agent to legacy platforms through the interfaces they expose and scope each permission to the agent’s task. Where a system has no interface, we flag it early, since it changes the design.
How do you test agents that work together?
We test at four levels, covering each agent’s accuracy, the context passed between agents, the business outcome of the whole system and drift after release. The handoffs between agents are where context gets lost.
Which industries have you built custom agents for?
Our work covers electric mobility, consumer goods, manufacturing and insurance, with agents for call summarization, field sales reporting, workforce GenAI access and lead conversion. The electric mobility case and the consumer goods case show the results.
How do you protect a custom agent from misuse?
We test every input for prompt injection and data leakage, give each agent only the tools it needs and require a person’s approval for actions with side effects. The build follows the agent-led development lifecycle and the checks in GATES.
Talk to our agent engineering team
Describe the workflow the agent would own and the systems it would touch. We will reply with how we would scope it and what the first release could cover.