AI Agent Development: Automate the Work Your Team Shouldn't Be Doing
From customer support to data processing to internal workflows — we build AI-powered automation that runs on your infrastructure, uses models you choose, and handles the repetitive work that slows your team down.
Book a Discovery CallYou're Paying Your Team to Do Work That Shouldn't Require a Human
Repetitive work costs your best people
Email triage, data entry between systems, weekly report assembly, support tickets answering the same 20 questions — AI agent development replaces each of these with automation, freeing your team for the work that actually requires judgment.
Agents handle the automation layer
Not "replace your team" — more like "stop paying a $60/hr operator to copy-paste data between systems." Agents triage, draft, extract, route, and update records without anyone touching it.
Built on open-source, on your servers
n8n and Windmill for orchestration, Ollama for local LLMs where privacy matters, Claude/GPT/Gemini where cloud models make sense. Everything runs on your infrastructure. Your data doesn't leave without permission.
What We Build
Customer-Facing AI Agents
Chatbots and support agents that answer product questions, triage support tickets, route inquiries to the right team, and handle common requests without human involvement. Built on your knowledge base, deployed on your website or internal tools, updated as your product evolves.
Internal Workflow Automation
Connect your internal tools — CRM, project management, Slack, email, databases — and automate the handoffs between them. Lead routing, invoice processing, data entry, report generation, alert escalation — designed around your actual workflows, not a generic template.
Data Processing & Document Intelligence
Extract structured data from PDFs, invoices, contracts, and emails. Classify, summarize, or route documents automatically. Connect to your existing storage (S3, Google Drive, SharePoint) and output structured records to your database or dashboard.
How an AI Agent Engagement Works
Discovery & Automation Audit
We map your current workflows, identify the highest-ROI automation candidates, and define what "done" looks like — what the agent does, when it escalates to a human, and how success is measured.
Agent Design
We design the agent architecture: which model fits the task, how context is managed, what data sources are connected, and where the human handoff points are. No code written until you've reviewed and approved the design.
Build & Integration
We build the agent logic, connect integrations, configure the LLM prompts, and set up the orchestration layer (n8n or Windmill) to handle scheduling, retries, and error handling.
Testing
We test against real examples from your operation — not synthetic data. Edge cases are documented and handled explicitly. Failure modes are defined.
Deployment & Monitoring
We deploy to your infrastructure, configure logging and alerting, and set up dashboards so you can see what the agent is doing, where it's succeeding, and where it needs tuning.
Why Work With iKemo for AI Agent Development
Model-agnostic, you pick the LLM
We don't lock you into one AI provider. Ollama for local privacy-sensitive tasks, Claude or GPT for complex reasoning, Gemini for Google ecosystem integrations. The right model for each job.
Your data stays on your servers
Agents run on your infrastructure. Sensitive documents, customer data, and internal records don't transit through our platform. You choose what goes to a cloud model and what stays local.
Built for your actual workflows
We don't sell you a pre-built bot and call it done. Every agent is built around your specific tools, data formats, and edge cases. If your CRM is unusual or your document formats are inconsistent, we handle it.
Designed with human escalation in mind
AI agents should make humans faster, not replace their judgment entirely. Every agent we build has clear escalation paths — when the agent isn't confident, it routes to a human with context instead of guessing wrong silently.
AI Agent Development — Frequently Asked Questions
What kinds of tasks are good candidates for AI automation?
High-volume, rule-based tasks with clear inputs and outputs are the best starting points: lead qualification, support ticket triage, invoice data extraction, report assembly, document classification, and internal request routing. If your team does it the same way every time, it's probably automatable.
Do you use OpenAI, Claude, or something else?
All of the above, depending on the task. We're model-agnostic — we pick based on cost, capability, and data sensitivity. For tasks where your data can't leave your infrastructure, we use Ollama to run open-weight models locally. For tasks that need frontier model capability, we use Claude or GPT with appropriate data handling.
How do you prevent the agent from making mistakes?
We design agents with explicit confidence thresholds and escalation paths. When the model is uncertain, it flags for human review instead of acting. We also build logging so you can audit every decision the agent makes. No silent failures.
What's the difference between this and using Zapier?
Zapier is excellent for simple, deterministic workflows — if X then Y. AI agents handle the unstructured, judgment-dependent tasks that Zapier can't: reading a free-text email and deciding how to route it, extracting data from a non-standard PDF, drafting a context-aware response. We often use both in the same pipeline.
Ready to Automate the Work That's Slowing Your Team Down?
Let's identify the highest-ROI automation opportunities in your operation and build agents that handle them — on your infrastructure, with models you control.
Book a Discovery Call