Connect AI to the systems that matter. We integrate chatbots and AI agents with your CRM, helpdesk, and business applications so they can do useful work.
AI that cannot access your business systems cannot do much useful work. Integration connects AI applications to the data and capabilities they need: your CRM, helpdesk, booking systems, databases, and custom applications. We make these connections reliable.
A chatbot that answers generic questions has limited value. A chatbot that can check a customer's order status, update their account, and book an appointment is genuinely useful.
The difference is integration. Connected AI applications can take real action, access real data, and fit into real workflows. Disconnected ones remain novelties.
We connect AI applications to virtually any business system with an API. Common integrations include:
CRM platforms: Salesforce, HubSpot, Microsoft Dynamics, Zoho. AI can access customer records, update information, log interactions, and trigger workflows.
Helpdesk systems: Zendesk, Freshdesk, ServiceNow, Jira. AI can create tickets, check status, route enquiries, and hand over to agents with full context.
Communication tools: Email systems, SMS gateways, Microsoft Teams, Slack. AI can send notifications, respond to messages, and coordinate across channels.
Business applications: ERP systems, booking platforms, e-commerce backends, custom databases. AI can access whatever information it needs to be useful.
Cloud services: Payment processors, shipping providers, identity verification, document generation. AI can trigger external services as part of workflows.
Integration projects follow a consistent methodology.
Requirements mapping documents exactly what the AI needs to do: which systems it must access, which data it must read and write, which actions it must trigger. This prevents surprises later.
Architecture design determines how connections will work: direct API calls, middleware layers, event-driven messaging, or hybrid approaches. The right architecture depends on your specific systems and requirements.
Secure implementation builds connections with appropriate authentication, encryption, and access controls. We follow security best practices and respect your existing policies.
Thorough testing verifies that integrations work correctly under normal conditions and handle errors gracefully. We test failure scenarios, not just happy paths.
Documentation and handover ensures your team understands what we built and can maintain it. Integration is infrastructure that needs ongoing attention.
Different use cases need different integration approaches.
Real-time lookup retrieves information on demand. When a customer asks about their order, the AI queries your system immediately and returns current status.
Action triggers make things happen. When an AI agent completes a sales qualification, it creates a record in your CRM and notifies the assigned salesperson.
Data synchronisation keeps information consistent. Changes in one system propagate to others so AI always has current data.
Event handling responds to external triggers. When a ticket is created in your helpdesk, AI can analyse it and suggest routing or responses.
We work with what you have. Integration does not require replacing your existing platforms or adopting new ones. Our job is connecting AI to your current technology landscape.
Sometimes legacy systems present challenges: limited APIs, poor documentation, authentication constraints. We have experience navigating these obstacles and finding workable solutions.
When AI is properly integrated, results improve across the board. Response times drop because AI can answer questions instantly instead of waiting for human lookup. Accuracy increases because AI accesses authoritative data sources. User satisfaction rises because interactions are productive, not frustrating.
The business case usually centres on time savings: tasks that took minutes now take seconds, and staff can focus on work that requires human judgement.
Use these prompts to define the minimum integration set and the controls needed for safe operation.
“Which systems must the AI read from and write to for this workflow to deliver value?”
“What permissions and audit requirements do we need for safe access to customer and operational data?”
“What failure modes should we design for: API outages, partial updates, incorrect data, and retries?”
Secure access to systems of record (CRM, helpdesk, databases), well-defined actions the AI can perform, and reliable error handling and auditability.
No. Most integration work is about connecting to what you already use.
Least-privilege credentials, scoped actions, validation, idempotency for writes, and monitoring so issues are detected early.
We assess options: middleware, event-driven patterns, or limited-scope automation. Where APIs are weak, we design around constraints rather than forcing brittle solutions.
We test the integration layer like any other system: realistic scenarios, failure cases, and safe staging environments where possible.