Service
AI Agent Development, Built With Guardrails
DartSol designs and builds AI agents that use your tools and data to complete well-defined tasks, with scoped permissions, human approval for consequential actions, and logging that makes every run reviewable.
Where AI agents are useful
- Support triage: classify incoming tickets, gather account context and draft a reply for an agent to approve
- Operations assistants: check order or job status across systems and open follow-up tasks
- Research and summarization over approved internal documents
- Sales and lead workflows: qualify inquiries against your criteria and route them to the right owner
- Internal helpdesk: answer staff questions from policies and runbooks, and escalate when unsure
How we architect a production agent
Tools and integrations
Agents act through explicit, well-defined tools: API calls to your CRM, ticketing, database or internal services. Each tool has a narrow purpose and validated inputs.
Scoped permissions
Each agent gets only the access its task requires, with separate credentials and no standing access to systems it doesn't need.
Human approval points
Consequential actions, like sending external messages, changing records or spending money, pause for a person to approve.
Grounded knowledge
Agents answer and decide from your approved data via retrieval (RAG), with source references where possible, rather than from model memory alone.
Evaluation
We test agents against realistic scenarios, including adversarial and edge cases, before launch, and re-run those tests when prompts or models change.
Monitoring and audit logs
Every run is logged: inputs, tool calls, outputs and approvals. That makes behavior reviewable and failures visible.
When an agent is the wrong choice
- The process is fully predictable. A deterministic workflow is cheaper and more reliable.
- A wrong action would be costly and can't be put behind human approval.
- The data the agent needs isn't accessible, or isn't approved for AI processing.
Our agent development process
- 1
Define the task
Agree on what the agent may do, what it must never do, and how success is measured.
- 2
Design tools & guardrails
Specify tools, permissions, approval points and fallbacks.
- 3
Build & evaluate
Build iteratively against a scenario test set until results meet the agreed bar.
- 4
Deploy & monitor
Launch with logging, alerts and periodic review of real runs.
Frequently asked questions
What is an AI agent?
An AI agent is software that uses a language model to decide which steps to take toward a goal, and then takes those steps by calling tools such as APIs, databases or search. Unlike a fixed workflow, it can adapt to the input. That's why it needs clear limits, permissions and oversight.
How is an AI agent different from a regular automation?
A regular automation follows the same predefined path every time. An agent chooses its path within boundaries you set. We often combine both: deterministic workflows for predictable steps, and an agent only where judgment over unstructured input is genuinely needed.
Which AI models do you use?
We choose models based on the task, data-handling requirements and cost, and we design so the model can be swapped later. Your data policies decide which providers are acceptable.
Can agents make mistakes?
Yes. Language models can be wrong or inconsistent. That's why we use narrow tools, validated inputs, human approval for consequential actions, evaluation before launch and monitoring after it. We don't promise fully autonomous or error-free operation.
How long does an agent project take and what does it cost?
It depends on the number of tools, systems and approval steps involved. After a consultation we provide a scoped estimate. We don't publish fixed prices.
Do you build AI agents for US companies?
Yes. DartSol LLC is registered in Austin, Texas, and works remotely with businesses across the United States, as well as in Canada and Australia.
Discuss Your Project
What happens next
- 1We review your request.
- 2We reply by email with any questions, or suggest a short call.
- 3If it's a good fit, you get a written quote for the agreed scope.
Prefer another way? Email info@dartsol.com or pick a time on Calendly (opens in a new tab).
DartSol LLC is registered in Austin, Texas, and works remotely with businesses across the United States, as well as in Canada and Australia.
Have a task an agent could handle?
Describe the task and the systems involved, and we'll tell you honestly whether an agent, a workflow or something simpler is the right fit.