We connect AI models and capabilities directly into your existing software stack — CRM, ERP, internal tools, or customer-facing platforms — with minimal disruption and maximum impact.
The biggest barrier to AI adoption in established businesses is not the AI itself — it is the integration. Your existing systems hold the data, workflows, and user interfaces that your team depends on every day. Replacing them is not practical.
ORCLOID specialises in connecting AI capabilities to the systems you already run — adding intelligence without disruption. Whether you need an LLM integrated into your helpdesk, a predictive model feeding your ERP, or a computer vision system connected to your manufacturing line, we handle the full integration layer.
We have built integrations across the most common enterprise and SMB platforms — and can connect to any system that exposes an API or database.
AI-enhanced CRM workflows: lead scoring, email generation, deal analysis, and customer insight surfaced directly inside your sales tools.
AI integrated into procurement, finance, HR, and supply chain modules — without replacing your core ERP investment.
AI assistants deployed inside your team communication platforms — answering questions, summarising threads, and triggering actions from chat.
AI product recommendations, dynamic pricing, customer segmentation, and support automation for e-commerce platforms.
Native integrations with cloud AI services, managed model endpoints, and serverless inference pipelines across all major cloud providers.
We integrate AI into bespoke internal applications — regardless of tech stack — via REST APIs, GraphQL, or direct database connections.
We handle the full integration layer — from API mapping to production deployment — so your team can focus on using the AI, not building the plumbing.
Discuss Your IntegrationWe map your current system landscape, identify integration points, assess data availability, and define the scope and success criteria for the AI integration.
We document every API endpoint, authentication method, data schema, and rate limit involved — building a complete picture before writing integration code.
We design the integration architecture — whether direct API connection, event-driven pipeline, or custom middleware — optimised for reliability, latency, and maintainability.
We build and test the integration exhaustively — unit tests, integration tests, load tests, and failure scenario simulation — before touching production systems.
We deploy to a staging environment that mirrors production, validate end-to-end data flows, and conduct user acceptance testing with your team.
We manage the production rollout with rollback capability, then hand over with full documentation, monitoring dashboards, and ongoing support.
Tell us which systems you need AI connected to and what the integration should achieve — we will map out the approach.