Enterprise AI Solutions, From the First Audit to Agents in Production
Your teams already have AI tools and a list of pilots. Ovidius AI tells you which process to automate first, builds the agents inside the ERP, CRM and helpdesk you already run, and keeps them working after launch, on self-hosted n8n in your own cloud. IES Limited, Pinkcube and GoKickflip run systems we built.
Enterprise AI Agents Built Into the Systems You Already Run
Each of these runs on self-hosted n8n and reads your systems through their APIs, with the permissions those systems already enforce.
Customer and employee chatbotsA chatbot that looks up orders, answers from your documentation and hands off to a person when it should. Pinkcube's support agent handles about 500 chats a week. See enterprise AI chatbots.
Finance and back-office agentsInvoices read, matched to the purchase order and posted to SAP, Odoo or any ERP with an API, with only the exceptions sent to your AP team. See AI invoice automation.
Scheduling and operations agentsAn agent that places 1,500 dental appointments a week across 200 practitioners on Odoo, and explains every slot it cannot fill. See AI agents in healthcare.
Agents that share one memoryYour data, tribal knowledge and operating rules in one governed layer, so every agent answers from the same source. See the enterprise context layer.
Enterprise AI That Stays Inside Your Cloud and Under Your Rules
Your security team will ask where the data goes and what stops a bad output. These are the answers, built into every workflow we ship.
Runs in your environment
Containerized n8n deployed inside your own cloud. For SSO, Git environments and log streaming, we set up n8n Enterprise.
Permissions inherited, retrievals logged
A finance agent cannot open payroll because the ERP already says no. The context layer records every read.
A second agent checks every draft
A guardrail agent screens inputs, a second agent checks outputs against your business rules, and actions above your threshold wait for a named approver. See enterprise AI governance.
Your own AI platform
Forge AI deploys, manages and scales AI tools, white-labeled under your brand.
How an Enterprise AI Engagement Runs
Every engagement follows the same four steps, and each one has a named owner on our side. The full process is on how we work.
Discovery callOwen, with Jason, hears the process you want to change and the systems it touches, and tells you whether AI is the right tool for it. Book it here.
AI AuditA fixed-fee engagement led by Jason that returns a scored readiness index, ROI models for your top three to five initiatives and a 90-day roadmap. See the enterprise AI audit.
Prove and buildMaciej's engineers build a prototype on your staging data, then take the approved workflow to production with its controls in place. See AI consulting.
Run and improveThe team that built the workflow monitors it, fixes it and reports what it saves. See AI managed services.
Enterprise AI Results From Systems in Production
GoKickflip · Content pipeline
A keyword in, a publish-ready article out 29 minutes later
A multi-agent pipeline on n8n that runs about 33 agent executions across six or more AI models for each article. It went from start to production in 30 days.
Scheduling for 200 practitioners after a year of failed native builds
For a Dutch Odoo implementation partner, an n8n agent places appointments nightly from a Supabase planning cache and explains every slot it cannot fill.
Working with Owen and the Ovidius team has been a seamless experience; they are incredibly responsive and adapted quickly to our specific requirements. By leveraging their AI-driven content for our travel insurance sites, we've completely phased out our reliance on external agencies and freelancers in 2026 while significantly speeding up production.
AI systems that do a defined piece of work inside a company's own processes and systems: reading invoices into the ERP, answering customers from the order database, scheduling staff, checking documents against policy. What separates them from a chat tool is that they run on company data, under company permissions, with an owner and a log. Our guide to AI consulting covers how companies choose which ones to build.
Where should an enterprise start with AI?
With one process that costs real hours and has clean enough data to automate. If you do not have that shortlist, start with the framework and checklist on our AI readiness assessment page, then take the shortlist into a fixed-fee AI Audit, which returns ranked use cases, ROI models and a 90-day roadmap. If you already know the use case, a proof of concept tests it on your staging data.
Where does our data go?
It stays in your environment. We deploy self-hosted, containerized n8n inside your own cloud, and agents read your systems through their APIs with the permissions those systems already enforce. The enterprise context layer page shows the architecture, and our healthcare context layer article applies it to protected health data.
Which systems do your AI agents work with?
Any ERP, CRM or helpdesk with an API. Builds on this site run on Odoo, SAP, HubSpot and Notion, and our n8n and SAP Joule Studio guide walks through one purchase-order approval flow end to end. You do not rebuild a database to add AI.
How long does an enterprise AI project take?
It depends on how many systems the workflow touches and how clean the data is, so we scope it before we quote it. The audit is its own engagement and ends with a 90-day roadmap, and a proof of concept typically takes 4 to 8 weeks. For a sense of build pace, GoKickflip's multi-agent pipeline went from start to production in 30 days; the GoKickflip case study has the details.
Can you train our teams as well as build for them?
Yes. Our corporate AI training is built on your team's own workflows, and n8n training prepares your engineers to maintain what we hand over.
Bring One Process to the Discovery Call
Pick the process that costs your team the most hours, or the AI pilot that never reached production. We will tell you whether AI fits it, which systems it touches and what the first step costs.
One partner, every layer
