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AI agent development

AI agents that take action and reach production, not another pilot that stalls.

Custom AI agent development for support, sales, and operations. We build autonomous agents wired into your real systems, CRM, helpdesk, billing, internal APIs, that don’t just answer, they do the work: check, update, route, resolve. Evaluated before launch, live in weeks.

Book a free consultation →Read the pilot-to-production playbook →

Serving SaaS teams, agencies, and growing businesses across the USA, Canada, and UK. Live in weeks, not quarters. For build and run-cost ranges, start with the AI chatbot cost guide.

What we build

Agents that do the work, not just talk about it.

Customer support agents

Resolve repetitive work end-to-end: look up an order, process a refund, update an account, reschedule a booking, then escalate the rest with full context attached.

Sales and lead-qualification agents

Engage inbound, ask the qualifying questions your reps repeat all day, enrich and route only sales-ready conversations into your CRM.

Operations and back-office agents

Agents that move data between systems, trigger workflows, reconcile records, and clear the repetitive queues that eat your ops team’s week.

Internal copilots and multi-agent workflows

Knowledge copilots and orchestrated multi-step agents that pull from your documentation and systems to complete work, not just summarize it.

Delivery approach

Production-first, with guardrails from day one.

Your agent connects to your systems of record, runs on an action allowlist, gets evaluated before it touches anything live, and ships with human handoff built in.
01

Discover

We map what the agent should own, what it must never touch, and which systems it connects to, and hand back a precise roadmap with a realistic estimate.

02

Build

A working agent early, integrated with your stack, grounded in your data, and evaluated against real cases in shadow mode before it acts on anything live.

03

Deploy and grow

Canary rollout, monitoring, tuning, then ongoing improvement or a clean handover. Typical launch: 2-6 weeks.

Who it fits

Built for teams with real volume.

  • →SaaS teams whose support or ops volume is scaling faster than headcount
  • →Agencies adding AI agent delivery for clients without building an engineering team in-house
  • →Sales teams losing hours to manual qualification an agent could pre-screen
  • →Operations and back-office leaders drowning in repetitive, multi-system tasks
Technical stack

Connected to your real systems.

We pick the model that fits the job, GPT, Claude, or Gemini, and build retrieval (RAG) for grounded answers, tool calling for actions, orchestration for multi-step flows, an evaluation harness, monitoring, and human handoff around it.

Proof

Proof from production.

Production-ready systems, not prototypes, evaluation before launch, monitoring after, and senior engineering measured by outcomes.
80%

tickets auto-resolved within 30 days

Daytronx, SaaS
3.4x

activation via conversational onboarding

WhatNextAI
Related resources

Related field notes and proof.

Playbook

Why AI agent pilots stall

The four reasons agents never leave proof-of-concept, and the checklist we use to get them to production.

Service

AI chatbot development

When you need answers rather than actions, production support and sales chatbots wired into your systems.

Case study

Daytronx: 80% of tickets auto-resolved

A production support agent that resolves work instead of routing it.

FAQ

Things teams ask us first.

Need a clearer answer? Ask directly. We reply within 24 hours.
What's the difference between an AI agent and a chatbot?
A chatbot answers questions. An AI agent takes action, it can look up an order, update a record, trigger a workflow, or complete a multi-step task across your systems, then escalate what it shouldn't handle. We build both; the difference is whether you need answers or outcomes.
How long does it take to build an AI agent?
Most agents go live in 2–6 weeks. A focused single-workflow agent with one or two integrations is 2–3 weeks; an orchestrated multi-agent system spanning several systems is 4–6 weeks. We ship a working version early so you give feedback before launch.
Why do so many AI agent pilots never reach production?
Usually because the agent was never connected to the systems where work happens, was never evaluated against real cases, or had no guardrails or handoff path. We build for production from day one, integrations, evaluation, allowlists, and escalation, so the agent ships instead of stalling.
Can the agent actually take actions, or just answer?
Take actions, within strict guardrails. We build scoped write access so the agent can update a record, process a refund, book a slot, or move data between systems, with an allowlist defining what it can do freely, what needs confirmation, and what always goes to a human.
Will it integrate with the tools we already use?
Yes, CRMs (HubSpot, Salesforce), helpdesks (Zendesk, Intercom), billing, scheduling, Slack, and custom internal APIs. Integration depth is exactly what separates an agent that completes work from one that only describes it.
How do you stop the agent from doing something wrong?
Three layers: grounded retrieval so answers come from your real data, an action allowlist so the agent can only do what it's authorized to, and a pre-launch evaluation suite that scores action-correctness on real cases. Anything outside the agent's authority escalates to a human with full context.
Which AI model do you build with?
Whichever fits your accuracy, latency, and cost requirements, GPT, Claude, or Gemini. We have no vendor allegiance; the engineering and evaluation around the model matter more than the model name.
What about our data security?
Encryption in transit and at rest, scoped access controls, and architecture that keeps your data out of model training. For regulated industries we design to your compliance requirements from day one.
Do we need a finished spec to start?
No. Most engagements start from a workflow that's painful and a rough idea. Discovery turns that into a scoped roadmap, a realistic estimate, and an honest pass/no-pass on whether an agent is the right fix.
Related services

Explore connected service pages.

AI agent developmentAI chatbot developmentRAG developmentVoice AI agentsWhatsApp chatbots

Ready to ship an agent that actually works?

One conversation. A precise roadmap, a realistic estimate, and a clear pass/no-pass on whether an AI agent is the right fix for the workflow you have in mind.

Get a free consultation →contact@theprocoders.com