Production AI for enterprises, MSPs and agencies

Everyone sells AI. We ship it.

We build agents and workflows inside the systems you already run, then keep them working after launch.

Try it: add your CRMLive
Your systems
Microsoft 365
HubSpot
OvidiusBuild, integrate, run
  • Read HubSpot and Microsoft 365
  • Map the data the workflow touches
  • Build and test it on your real data
  • Deploy in your cloud, behind your auth
  • Alerts and logs to your team

Clients include

AudinatePinkcubeBizIQCourserAllClear

Four builds, measured before and after

Each one is written up in full on its case page: what the work cost or took before, and what it costs or takes now.

See all case studies
GoKickflipE-commerce and SaaS, content pipeline
$700$12.11
Cost per publish-ready article

A keyword in, a publish-ready article out, in 29 minutes

Three agents on n8n research, brief and write each article with a multi-model stack, so output scaled without hiring. Built and shipped in 30 days.

98%lower cost per article
10xmonthly output
$358Ka year saved at equal volume
Read the GoKickflip case

From day one, the Ovidius team moved fast, thought big, and executed with precision.”

Renaud TeasdaleRenaud TeasdaleCEO, GoKickflip
PinkcubeB2B e-commerce, after-hours chat agent
45 h168 h
Chat coverage a week
Staffed, 45 hCovered by the agent, 123 h

Every evening and weekend answered, and a second AI vets each reply

7.7 smedian first response
704conversations handled
4.6/5across 76 hostile test scenarios
Read the Pinkcube case
IES LimitedInsurance, daily MI alerting
20 days30 min
Time to detection

A 25-page MI pack nobody finished, read in full every working day

1,751metric evaluations
4 of 4replayed incidents caught
34threshold changes, zero tickets
Read the case
IES LimitedInsurance, content engine
4 brands1 engine
One compliance-first pipeline
  • Brand A
  • Brand B
  • Brand C
  • Brand D
Compliance Checker AgentAudits every draft against each brand's banned terms, then a person reviews it
80%less manual production effort
0external agencies in 2026
11stages automated

We've completely phased out our reliance on external agencies and freelancers in 2026 while significantly speeding up production.”

Bhavek RughaniBhavek RughaniHead of Marketing, IES Limited
Read the IES content case

Most AI never reaches production

88%

of AI proofs of concept never reached production: 4 out of 33

Source: Lenovo CIO Playbook 2025, with IDC
See the AI Audit

Four places where AI projects stall, and the step we take before or during a build for each.

The problem was never tested

Phase 1 of the AI Audit tests the problem and the mandate first. If you already know the workflow, scoping does the same job in days.

The pilot never met the real systems

We build against your real data, inside your environment, from the first week. Phase 2 of the audit maps how data moves between your systems.

Nobody set a baseline

Phase 7 models ROI before you commit budget, and every system we ship reports what it saves.

The model got more access than its users

Agents run behind your own auth and read only what your permissions allow. Phase 5 scores governance and access posture.

AI systems we build and run

Each runs on self-hosted n8n with the model that suits the task. See every solution

Enterprise AI chatbot

Answers from your order database, CRM and help center, hands off to a person when it should, and has every reply checked by a second agent before a customer sees it.

500 a weekPinkcube: about 500 support chats a week, one of twelve production systems we run for them
Customer asksChat, email or your help widget
Agent reads your systemsOrders, CRM, help center
Second agent checksEvery reply, before it is sent
Answer or handoffTo a person when it should
Example runWhere is order #4821?Shipped Tuesday, arriving Friday. Tracking link sent.Checked by second agent
Connects to ZendeskHubSpotSalesforceShopify
Enterprise AI chatbot

Pick the page written for your team

Each one covers what we build for that kind of team, who owns it and the proof behind it.

Enterprise teams

Find the workflows worth automating, then run them in your own cloud.

MSPs

Six AI services your clients buy from you, delivered by us under your name.

Agencies

Delivery pipelines that cut production cost, and AI tools you sell under your brand.

Teams on n8n

New builds, a review of what you already run, or training on your own workflows.

Every service, in the order teams use it

Decide

Find the processes worth automating and plan the order.

AI AuditAI readiness assessmentEnterprise AI strategyEnterprise AI roadmap
Build

Agents and workflows inside your systems, on your data.

Enterprise AI chatbotAI invoice automationEnterprise context layern8n workflows and agents
Run

Monitored, governed and improved by the team that built it.

AI managed servicesEnterprise AI governancen8n review and hardening
Grow

Train your team, or sell AI under your own brand.

Corporate AI trainingn8n trainingForge AI platform

One line from first call to a running system

Five stages, each with one partner who answers for it. See how we work

How long does it take?

  1. Jason
    Jason, COO

    AI Audit, if needed

    Eight phases across strategy, operations, data, systems and governance, ending in a ranked 90-day roadmap.

    • ROI models for your top three to five initiatives
    • A ranked 90-day roadmap you own
    • Fee credited toward your first build
  2. Jason
    Jason, COO

    Scope

    One workflow, the systems it touches and what it will take, agreed before you commit. Owen joins the first calls until you are onboarded.

    • A written scope: workflow, systems and data
    • What it will take, before you sign
    • A proof of concept first, where the risk sits in your data
  3. Maciej
    Maciej, CTO

    Build

    Built against your real data, in your environment, as production software from the first week.

    • Self-hosted n8n in your cloud
    • The model that suits each task
    • Your data stays where it is
  4. Jason
    Jason, COO

    Integrate

    Into production behind your auth, your governance and your monitoring, with your team trained on it.

    • Runs behind your own auth
    • Alerts and logs to your team
    • Your people trained on the system
  5. Maciej
    Maciej, CTO

    Run and improve

    Watched, fixed and extended in weekly sprints by the engineers who built it.

    • Weekly sprints that you direct
    • A report of what each workflow saves
    • The next use case, scoped with you

Forge AI

Sell AI under your own brand

Forge AI is the white-label platform behind our builds. MSPs and agencies deploy it per client, under their own domain, with each client's data kept apart.

  • Your brand, your domain
  • Every client in one console
  • Each client's data kept apart
  • Billed monthly, sold as yours
Your recurring revenue with Forge AI
$5,000Recurring a month
$60,000Recurring a year

Your inputs, your pricing. The calculator multiplies them and makes no claim about what clients pay.

What teams ask us first

Ask us something else

Why do you scope one workflow at a time?

Because a workflow can be finished and measured. We agree the workflow, the systems it touches and what it will take before you commit, and the second use case is easier because the first one is already running.

Does our data have to leave our environment?

No. We build on self-hosted n8n in your cloud, behind your own auth, and agents read your systems through their APIs with the permissions your people already have.

What if we don't know where to start?

Start with the AI Audit. Jason runs eight phases across strategy, operations, data and systems and hands you a ranked 90-day roadmap. The fee is credited toward your first build.

Which models do you use?

The one that suits the task. GoKickflip's pipeline runs about 33 agent executions across six or more models for each article, and the routing is part of what we maintain.

Can we resell what you build?

Yes. MSPs and agencies deploy Forge AI per client under their own brand, and we deliver the build behind it. See AI for MSPs and AI for agencies.

What happens after the first workflow is live?

The team that built it runs it: monitoring, fixes and the next use case, in weekly sprints that you direct.

Put your first workflow on the board

Answer a few questions about your team and what you want automated, then Jason scopes it with you on the call.

Owen, Maciej, Jason, Oskar and Ben