Gaper

Production AI agents built into everyday workflows

Production AI agents built into the workflows a business already runs. AI agents that run inside a client's existing tools are designed, built and launched by Gaper, an implementation partner in this field. The starting point is a single operation that is losing hours or dollars, rather than an AI category. Gaper maps that workflow, builds an agent to handle it, measures the savings and then hands the working system to the client's team to run.

Where the agents are deployed

Gaper names several operating lanes where agent work usually pays off. In customer support, tickets move between a helpdesk, policy documents, order data and human approval, and an agent can resolve the case, update it and escalate with full context. In finance and accounting, close work stalls on matching, exceptions and approvals, and an agent can reconcile transactions, chase exceptions and prepare the close faster. In sales operations, leads, CRM updates, research and handoffs sit between tools, and an agent can enrich and score leads, update the CRM and prepare reps before calls.

Document processing is another lane, where PDFs, emails, forms and attachments create manual review queues that an agent can read, validate against other systems and route. Internal knowledge work covers staff who ask the same questions while the answers are spread across stale documents, which an agent can answer with citations and clear handoffs. Regulated work in healthcare, legal and accounting operations needs judgment, audit trails and human review, so the agents are launched with approvals and decisions that can be traced.

Savings Gaper reports from earlier work

Gaper reports results from earlier engagements, each tied to one measurable metric. In healthcare scheduling, it reports 15 to 30 percent fewer no-shows as agents fill empty slots and recover lost capacity. In legal intake, it reports that qualification, routing and follow-up moved out of manual queues, cutting intake admin by 60 percent. For accounting, it reports close preparation about five times faster, and for revenue and operations work, quotes about three times faster. These are the company's own figures, and each is presented as a result it has delivered before.

How an agent is built and handed over

Gaper builds each agent in stages: it scopes the workflow, builds the tools the agent needs, gates the agent with evaluations and then moves it to go-live. Its material gives a first build within 24 hours, with 12 evaluations and release gates before anything goes live. Each agent is given tools, permissions, escalation paths and an owner in production before users depend on it.

Agents run in the client's own cloud, using the client's authentication and data. Gaper says the client receives the code and a runbook at handover, with no platform lock-in. The agents are model-agnostic and can draw on several large language model providers, including OpenAI, Claude and Gemini.

Starting with a free assessment

The first step is a free 30-minute workflow teardown, with one savings case as the output. Gaper frames the assessment as a way to see where an agent would pay off in a client's own operation before any build begins, and it works from whichever metric matters most to the client, such as the number of missed appointments or the time spent building quotes.