Custom AI Agents

An AI automation agency maps how a workflow runs today, builds an agent that handles the repeatable slice of it, wires the tool connections and source records the agent needs, and maintains the system after go-live with monitoring, quality checks, and model updates. All four parts matter. An agency that only does the third one has sold you a tool, not an automation.

No, but it usually pays for itself. If you have done the Audit, the build starts from a ranked, costed roadmap and the scoping work is already half done. If you come straight to a build with a workflow your team can name, we scope it from scratch: the steps, the volumes, the handoffs, the systems it touches. Either way, scope and price are fixed before work starts, and if something will not hold, an integration or a data gap, we tell you at scoping rather than mid-build.

An AI automation agency builds the system: the agent, the tool connections, the source records, and the handover notes. An AI consultant scopes the opportunity and tells you where AI would move a business metric, without necessarily building anything. If you already know you want a done-for-you build, the agency is the right door. If you're still working out whether the case exists, an advisory engagement is the earlier, cheaper step.

Plan for 50 to 80 percent of the operator time on a given workflow, not the whole role. Your reconciliation analyst still owns the judgment calls. The agent handles the repetitive middle of her week. We won't sell you full automation because full automation does not land in mid-market ops.

The honest range is wide: a narrow, well-defined agent from a small in-house team can land in the low hundreds of thousands of dollars, while a broader build touching multiple systems runs higher. What moves the number is scope, whether the team is in-house or subcontracted offshore, and whether pricing is fixed-scope or open-ended time-and-materials. A fixed-price discovery phase, priced before the build, is the fastest way to turn that range into a real number for your workflow.

If you have a senior technical team with real capacity, build it. Most operators do not. You have the domain knowledge and the records; we bring the agent, system connection, and quality-check experience, then hand the system back at the end.

It depends on whether you have a senior technical team with real spare capacity and a quality-check process already in hand. Most mid-market operations do not, which is why they bring in a build partner rather than staffing up from zero. The workflow's specificity matters too: if an off-the-shelf tool already covers it well, buying beats building or hiring either way.

The build runs inside your environment and is governed by the engagement terms. At handover you receive training, runbooks, quality checks, and operating notes. Ongoing coverage through Operate is optional, not a leash.

Ask six questions of anyone you're shortlisting: do they build in-house or subcontract; is there a fixed-price, named discovery deliverable; what do you receive at handover; are there quality checks and monitoring after go-live; do they name what stays human instead of promising full automation; and do their case studies cite business metrics rather than only development metrics. An agency that answers all six plainly is worth a serious conversation.

The system runs single-tenant with data stored in the region you require, and your records are never used to train shared models. Where the engagement needs deployment inside your own boundary, we scope it that way from the start. Every important source lookup and decision is logged.

The Audit runs 1 to 3 weeks and ends with a costed roadmap. Build is typically 7 to 17 weeks after scope is signed, depending on integrations and data readiness. The combined path is scoped to keep Audit plus Build inside an 8 to 20 week delivery window where the workflow allows it.