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Custom AI Agents

An AI agent is software that perceives inputs, reasons about them using a language model, and takes actions in external systems without constant human direction. For mid-market teams, AI agents handle structured, high-volume tasks: resolving support tickets, processing documents, enriching CRM records, and orchestrating multi-step back-office workflows.

Last reviewed: February 2026

We build autonomous AI agents for 10–200 employee teams that handle support tickets, process documents, enrich CRM data, and run back-office workflows, plugged directly into the tools you already use. You get a deployed system, not a proof of concept.

Who is this for?

Teams with 10–200 employees that have outgrown manual processes but aren't ready to build an in-house AI team. Specifically:

  • ◆Support teams handling repetitive ticket categories that could be auto-resolved
  • ◆Operations teams processing documents (invoices, contracts, intake forms) by hand
  • ◆Sales and marketing teams manually enriching leads or updating CRM records
  • ◆Any team where a human is doing the same structured task more than 20 times a week

What do you get?

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A production-ready AI agent deployed in your environment

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API integrations with your existing tools (CRM, helpdesk, ERP, etc.)

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Escalation and human-in-the-loop workflows for edge cases

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Monitoring dashboard with accuracy, latency, and throughput metrics

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Documentation and runbooks for your team

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30 days of post-launch support and tuning

What does the timeline look like?

01

Discovery

Week 1

Map your workflows, data sources, and integration points. Define success metrics.

02

Build

Weeks 2–3

Develop the agent, connect APIs, implement escalation logic. You see working demos weekly.

03

Pilot

Week 3–4

Run the agent on live data alongside your team. Measure accuracy and tune thresholds.

04

Deploy

Week 4+

Production deployment, monitoring, team training, and 30 days of post-launch support.

What are the common pitfalls?

Starting too broad

Teams that try to automate every workflow at once stall. We scope a single high-impact use case first, ship it, then expand.

Ignoring data quality

AI agents are only as good as the data they work with. If your knowledge base is outdated or your CRM is full of duplicates, the agent will inherit those problems. We audit data quality before building.

No escalation path

Agents without clear fallback logic erode trust fast. Every agent we build includes configurable confidence thresholds and human escalation routes.

Treating AI as a black box

If your team doesn't understand what the agent does and when it hands off, adoption dies. We provide observability tooling and plain-language documentation.

FAQ

What kind of tasks can an AI agent handle?

Structured, repeatable tasks: answering support tickets from your knowledge base, classifying and routing inbound requests, extracting data from documents (invoices, contracts, forms), enriching CRM records from public sources, and orchestrating multi-step workflows across your SaaS tools.

Do I need to replace my existing software?

No. Agents connect to the tools you already use (Salesforce, HubSpot, Zendesk, Slack, Google Workspace) through APIs. The goal is to automate work inside your current stack, not rip and replace it.

How accurate are AI agents compared to a human?

It depends on the task. For structured classification and extraction, well-built agents routinely exceed 95% accuracy. For open-ended judgment calls, we design human-in-the-loop checkpoints so edge cases get routed to your team.

What happens when the agent can't handle something?

Every agent includes escalation logic. When confidence drops below a configurable threshold, the task routes to a human with full context attached. You stay in control: the agent handles volume, your team handles exceptions.

How long does it take to get a working agent in production?

Most single-agent projects go from kickoff to production in 4–12 weeks. A scoped pilot (one ticket category or one document type) can ship in as little as a single week. Multi-agent systems typically take 8–12 weeks.

Ready to put an agent to work?

Book a free 20-minute discovery call. We'll map your highest-impact use case and scope what a pilot looks like.

Book a Strategy Call →

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