AI agents that work inside your existing systems
We build AI agents that can look things up, take actions in your systems and hand over to a person when they should. Typical examples are customer support assistants that check real order data, and internal assistants that answer questions from your own documents.
At a glance
- Typical timeline
- 8 to 14 weeks for single agents. 12 to 20 weeks for multi-agent systems. Ongoing maintenance required.
- How we price
- Fixed price for an agreed scope, after a short discovery
- Technology
- Python, LangChain, LangGraph, CrewAI, OpenAI API, Anthropic Claude API
What this usually looks like
Customer Support Agent
An AI agent that accesses your knowledge base, CRM, and order system to resolve customer queries, process returns, and escalate complex issues to human staff.
Lead Qualification Agent
An AI agent that engages website visitors, qualifies leads against your criteria, and books discovery calls directly into your calendar.
Document Processing Agent
An AI agent that reads contracts, extracts key terms, flags risks, and populates your legal management system automatically.
Internal Operations Agent
An AI agent that monitors dashboards, generates reports, sends notifications, and coordinates tasks across departments.
Sales Research Agent
An AI agent that researches prospects, enriches CRM records, and prepares personalised outreach drafts for your sales team.
Compliance Monitoring Agent
An AI agent that scans communications and transactions for regulatory compliance issues and generates audit reports.
What you can expect
- Provide 24/7 customer support with human-level contextual understanding
- Qualify leads and book meetings autonomously during and outside business hours
- Process and respond to emails, support tickets, and enquiries in seconds
- Execute multi-step workflows across multiple systems without manual coordination
- Maintain consistent service quality regardless of volume or time of day
- Reduce customer response time from hours to seconds
How the project runs
Agent Design Workshop
Elsio works with your team to define the agent's purpose, capabilities, decision boundaries, and integration points.1 to 2 weeks
Knowledge Base & Context Engineering
Elsio structures your business knowledge, documents, and processes into a format optimised for AI agent retrieval and reasoning.2 to 3 weeks
Agent Development & Tool Integration
Elsio builds the agent with appropriate LLM backbone, tool-use capabilities, memory systems, and connections to your business systems.3 to 6 weeks
Supervised Deployment & Tuning
Elsio deploys the agent in supervised mode, monitors performance, adjusts behaviour, and transitions to autonomous operation.2 to 3 weeks
What you receive
- Agent architecture and scope document
- Trained AI agent with tool-use capabilities
- Knowledge base and retrieval system
- Integration with business systems
- Monitoring and analytics dashboard
- Agent behaviour documentation
- Human escalation workflow
- 90-day supervised operation and tuning
Is it the right choice?
An agent is not the answer to every problem. If a simple form, a better FAQ or a fixed workflow would solve it, that is cheaper and more reliable. Agents earn their place when requests vary a lot, need information from several systems, and are too frequent for staff to handle quickly.
Strengths
- Operates autonomously 24/7
- Handles complex multi-step workflows
- Integrates deeply with business systems
- Learns and improves from interactions
- Scales without proportional cost increase
- Provides consistent service quality
Trade-offs to plan for
- Requires ongoing LLM API costs
- Edge cases may need human intervention
- Knowledge base needs regular updates
- Initial setup requires significant domain expertise
- Performance depends on quality of training data
- Regulatory considerations in some industries
Custom AI agents vs Traditional Chatbot
| Factor | Custom AI Agents | Traditional Chatbot |
|---|---|---|
| Autonomy | Plans and executes multi-step tasks independently | Responds only when prompted |
| Tool Use | Accesses CRM, email, databases, APIs | Text responses only |
| Memory | Remembers context across conversations and sessions | No persistent memory |
| Decision Making | Evaluates options and chooses optimal actions | Pattern-matched responses |
| Integration Depth | Deep integration with business systems | Surface-level chat widget |
| Business Impact | Handles end-to-end workflows | Deflects support tickets |
Common questions
What is an AI agent?
What is the difference between an AI agent and a chatbot?
How is AI agent development priced?
Are AI agents safe and reliable?
Can an AI agent access our existing systems?
How long does it take to build an AI agent?
Talk to us about AI agents
Send a short brief and we will come back with questions, a rough approach and whether we are the right fit. No sales sequence.
Prefer email? info@elslabs.co.uk
Or message us on WhatsApp.