A custom AI agent handling customer queries, following up leads, processing orders and managing internal tasks across Slack, Salesforce, Shopify, Gmail, Notion and HubSpot

Agentic AI

Custom AI Agent Development Services

A custom automation AI agent is an autonomous assistant built around one of your business processes — support triage, lead follow-up, order handling or internal operations — trained on your own policies and connected to your existing tools so it can take real actions, not just answer questions. Human-in-the-loop escalation keeps ownership with your team.

AI agent development: agent types, where agents run, cost and timing

Book a Strategy Call All services

24/7

autonomous operation

6-12 wks

typical discovery to production for a first agent

1-2

systems connected in a typical first agent

The problem today

Generic chatbots that answer questions but cannot complete a task
Repetitive workflows depending on one person's availability
Leads and tickets going cold outside business hours
Automation rules too rigid to handle real-world variation in requests

Outcome

Businesses run support, follow-up and back-office workflows around the clock with agents trained on their own processes.

Tailored AI agents that automate repetitive workflows and integrate with your existing tools.

How we deliver it

Step 1

Scope

One high-value workflow selected, with success metrics, guardrails and escalation rules defined.

Step 2

Train

The agent is grounded in your SOPs, product data, tone of voice and historical conversations.

Step 3

Connect

Tool access wired to CRM, helpdesk, database and internal APIs so the agent can act, not just reply.

Step 4

Launch & tune

Shadow mode first, then supervised release, with weekly review of transcripts and outcomes.

What's included

Workflow automation

Multi-step tasks executed end to end with retries, logging and deterministic guardrails.

Tool & CRM integrations

HubSpot, Salesforce, Slack, Zendesk, databases and internal APIs available as agent actions.

Trained on your logic

Grounded in your SOPs, pricing rules and policies so answers reflect how you actually operate.

Human-in-the-loop

Confidence thresholds and approval steps route edge cases to a person with full context attached.

What you receive

Workflow specification and guardrail policy
Trained agent with grounded knowledge base
Tool and CRM integrations with action logging
Evaluation suite and transcript review dashboard
Ongoing tuning and retraining plan

Frequently asked questions

How is an AI agent different from a chatbot?

A chatbot replies with information. An agent plans multi-step work and takes actions in your systems — updating a CRM record, issuing a refund, booking a slot — within guardrails you define.

What data is needed to train an agent?

SOPs, product and pricing information, policy documents and a sample of historical tickets or conversations. Two to three weeks of clean examples is usually enough to start.

How do you stop the agent making mistakes?

Deterministic guardrails on sensitive actions, confidence thresholds, approval steps for high-impact operations, full action logging and an evaluation suite run before every release.

Which systems can it integrate with?

HubSpot, Salesforce, Zoho, Zendesk, Freshdesk, Slack, Shopify, Google Workspace, Microsoft 365 and any internal system exposing an API.