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AI Agents
Custom AI agent development for customer support, sales, data analysis, and business operations.
What's Included
- Customer Support Agents
- Sales Qualification Agents
- Data Analysis Agents
- Research Agents
- Multi-Agent Systems
- RAG Implementation
- Tool-Using Agents
- Custom Agent Training
Chatbots built on decision trees and keyword matching break the moment a user says something unexpected. They frustrate customers, generate negative reviews, and end up abandoned after 3 months because the maintenance overhead is too high. Modern AI agents are fundamentally different — they can reason, use tools, access databases, and handle conversations that would previously require a trained human agent.
We build AI agents using the latest large language models (Claude 3.5 Sonnet, GPT-4o) with tool use, RAG (Retrieval Augmented Generation) for your specific knowledge base, and human escalation logic. Our agents are trained on your exact product catalogue, policies, pricing, and FAQs — they give accurate, consistent answers every time. We also build multi-agent systems for complex workflows where different agents handle different parts of a process in coordination.
Exactly What You Get
Every AI Agents project includes these specific deliverables. No vague scope, no hidden extras.
Agent Knowledge Base
Structured knowledge base built from your FAQs, product documentation, policies, and past support tickets. Used by the AI to answer questions accurately.
Conversation Design
Every conversation flow mapped: greeting, intent detection, question answering, escalation triggers, and handoff logic to human agents.
Built & Integrated Agent
Production agent deployed to your website, WhatsApp, Slack, or other channels. Connected to your CRM, order management, or ticketing system.
Human Escalation System
Rules for when the agent transfers to a human: expressed frustration, sensitive topics, high-value sales enquiries, or out-of-scope questions. Handoff includes full conversation transcript.
Analytics Dashboard
Metrics for agent performance: resolution rate, escalation rate, CSAT scores (if collected), most common intents, and unanswered questions.
Pricing Framework
Customer support AI agent builds start at $1,500 for a simple FAQ and ticket routing agent to $8,000+ for a full-service agent with CRM integration, order management, and human escalation routing. Sales qualification agents with CRM write-back typically run $2,500–$6,000. Monthly AI agent maintenance (prompt updates, knowledge base refreshes, performance monitoring) starts at $349/month.
Our Process
How we deliver AI Agents projects from kickoff to launch.
Use Case Definition
Define the agent's role, capabilities, knowledge base, and escalation rules.
Architecture
Design agent architecture: LLM choice, memory, tools, and guardrails.
Development
Build the agent with RAG knowledge base, tool integrations, and conversation flows.
Testing
Test with real-world scenarios, edge cases, and adversarial inputs.
Deployment
Deploy and monitor agent performance, accuracy, and escalation rates.
Real Results From Real Clients
Numbers from actual AI Agents projects we have delivered.
500+ daily student support inquiries, 6-hour average response time, CSAT declining, and support team at capacity.
AI agent on Claude 3.5 Sonnet handles 70% of tickets autonomously. Response time: under 30 seconds. CSAT: 4.8/5 (up from 3.2/5). Support cost reduced 60%.
Technologies We Use
Frequently Asked Questions
Everything you need to know about our AI Agents service.
What are AI agents and how are they different from chatbots?
Traditional chatbots follow scripted decision trees — they can only respond to the specific questions they were pre-programmed to handle. AI agents use large language models to understand intent, reason about the right response, use tools (search your database, create a ticket, look up an order), and maintain context across a conversation. They handle unexpected questions gracefully rather than sending 'I don't understand that' for the tenth time.
What can an AI agent do for my business?
Common AI agent applications: customer support (answer product questions, process simple requests, escalate complex issues), sales qualification (ask discovery questions, score leads, book meetings), internal knowledge assistant (answer employee questions about policies, process, and documentation), order management (look up order status, initiate returns, provide tracking updates), and research (gather, summarize, and present information from multiple sources).
How accurate are AI agents?
Accuracy depends entirely on the quality of the knowledge base and how well the agent is configured. An agent trained on your exact product catalog, policies, and FAQs typically achieves 85–95% accuracy on in-scope questions. We measure accuracy during testing and document it before go-live. For out-of-scope questions, the agent gracefully acknowledges the limitation and escalates.
What channels can an AI agent be deployed on?
We deploy agents on: website chat widget, WhatsApp Business API, Slack (internal agents), Facebook Messenger, email (incoming email classification and auto-response), and via API for custom integrations. Most agents are deployed on website chat as the primary channel first, with additional channels added later.
How do you keep an AI agent's knowledge up to date?
We set up a knowledge base management system where your team can update FAQs, product details, and policies. Monthly knowledge base refresh is included in our maintenance retainers. We also monitor the questions the agent cannot answer and add them to the knowledge base proactively.
Further Reading
In-depth guides related to AI Agents.
Related Services
Ready to Get Started with AI Agents?
Book a free consultation and let's discuss exactly what your project needs.