Custom AI Agent Development

Autonomous AI agents that qualify leads, handle support, and automate workflows — 24/7, without human intervention. Not flowcharts or chatbots. Real agents that reason, adapt, and take action.

40+ production AI agents deployed Avg. 94% task completion rate First results in 2-3 weeks

Sound Familiar?

Leads going cold because your team cannot respond in under 5 minutes
Support tickets piling up while your team works on "real" issues
AI demos that work in PowerPoints but fail in production
Building AI in-house takes months and you still need ML expertise
Case Study

Custom Agent Handles Legal Research in 90 Seconds

The Situation

A law firm was spending 8 hours per case on research. Junior associates were overwhelmed, senior partners burned out.

The Approach

Built a research agent that reads case files, queries legal databases, and drafts research summaries. Output reviewed by attorneys, not written by them.

90 sec vs 8 hours manual
95% accuracy rate
$40k annual savings per attorney

"We tried building in-house for 6 months. Jose shipped what we needed in 3 weeks. The agent handles 200+ support tickets daily now."

— Sarah Kowalski, Head of Product at LegalTech AI

What You Get

85% faster response time
60% cost reduction vs manual
24/7 consistent availability

How It Works

1

Map the workflow

We document exactly how the task should be done. What decisions are made? What data is needed? What happens next?

2

Design the agent

Define tools, memory, decision logic, and guardrails. How does it know when to act? When to escalate?

3

Build & validate

First working version in 2 weeks. Real outputs tested against real scenarios. Iterate until accuracy hits 90%+.

4

Deploy & monitor

Launch to production with logging and alerts. Review outputs weekly. Improve continuously.

Ready to Get Started?

Book a free 15-minute call to discuss your project. No commitment, no sales pitch — just an honest conversation about what you need.

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Common Questions

How is a "custom" agent different from using ChatGPT or Claude?

Public AI models are general-purpose. A custom agent is trained on your specific data, integrated with your tools, and configured for your workflows. It knows your products, your processes, your customers — not generic knowledge.

What data do you need to build a custom agent?

Typically: documentation, FAQs, product info, process guides, example conversations. For better accuracy, labeled examples of good/bad outputs help. I can work with whatever you have and improve over time.

How long does custom agent development take?

Minimum viable agent: 2-3 weeks. Production-ready with full testing: 4-8 weeks. Timeline depends on complexity, integration needs, and how much fine-tuning is required.

Can the agent be updated as our business changes?

Yes. Agent behavior, knowledge base, and tools can be updated without rebuilding from scratch. I set up easy processes for your team to maintain it.

What if the agent starts behaving unexpectedly?

Monitoring catches anomalies. Rollback mechanisms return to previous behavior. I also set up "circuit breakers" that pause agent action if confidence drops below thresholds.