AI Integration Services
We put AI inside the tools your team already uses: documents that turn into ERP records, voice notes that become orders, assistants that can safely read and write your CRM. Built, deployed and run by the same senior team, with prices published below.
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What are AI integration services?
AI integration services connect an AI model to the systems a business already runs, such as the ERP, the CRM, the inbox or the messaging channel, so that it does one specific job inside an existing workflow. The value is never the model on its own. It is the plumbing around it: reading your real data, writing back to the right record, asking a person to confirm when it matters, and logging what it did.
Most companies that ask us for AI already tried a chatbot or a standalone tool. What they need is narrower and more useful: the order typed in automatically, the invoice filed in the ERP, the CRM updated after the meeting, without anyone copying data between windows.
What we integrate
Four shapes come back again and again. Each one below is work we have shipped, not a capability slide.
Documents into your ERP
Orders, invoices and quotes arrive by email, PDF or photo. A vision model reads them, drafts the ERP record, and a person approves before anything is written. We read an insurer's entire claims book this way: 13,000 documents, 96% of them photos.
What 13,000 claim documents looked like →Voice and WhatsApp into orders and the CRM
For Qortex, a retail platform in the UAE, we built the engine that turns WhatsApp voice notes in Arabic and English into structured orders, matched to each merchant's own catalog. The same pipeline updates a CRM from a voice note recorded after a meeting.
The Qortex case study →AI assistants inside your systems
We build MCP servers that let assistants like Claude read and write Salesforce, HubSpot or a custom CRM through typed, permissioned tools, with a confirmation step before revenue-critical writes. Our own runs 91 tools from one server.
How one server runs 91 tools →AI on infrastructure you control
When data cannot go to a third-party API, the model runs on infrastructure you control, in the region you need, with the same integrations around it.
Sovereign AI options →How an AI implementation runs
Four stages. Something useful is in production at the end of the second one.
- 1
Scope one workflow
A short audit of the process you want to change: the data it uses, the systems it touches, what a wrong answer costs, and whether AI is even the right tool. Sometimes it is not, and you hear that first.
See the AI audit in detail → - 2
Pilot in production
The first workflow built end to end on your real data, with a human review step, measured against an agreed success criterion. Not a demo environment.
- 3
Widen
More document types, more intents, fewer reviews where the error rate allows it. Each step is decided on measured accuracy, not on enthusiasm.
- 4
Run it
Hosting, monitoring, model updates and changes as your process moves. Models change every few months; someone has to re-test the workflow when they do.
How much do AI integration services cost?
Our published prices, converted to US dollars. Most firms in this market quote only after a sales call.
| Scope | Indicative budget | What you get |
|---|---|---|
| Express scoping (one workflow) | $2,300 to $4,700 | A half-day workshop on one process, a written summary, and a clear answer on feasibility and the pilot's size. |
| Full AI audit | $7,000 to $14,000 | Your use cases ranked by return and effort, the model choice for each, and a scoped pilot with its success criteria. |
| Audit plus a pilot in production | from $17,500 | The audit, then the first workflow built through to production, with your team trained on it. |
| Running it afterwards | from about $470 per month | Hosting, monitoring, re-testing when models change, and a monthly allocation of changes. |
These figures are indicative and firm up after a first conversation. The audit is credited against the pilot if you build it with us. Model usage (the API calls themselves) is a separate line in the quote, and is usually small next to the build.
What is the difference between AI integration and AI implementation?
In practice the terms overlap, but the distinction is useful when you compare quotes. AI integration is the technical work of connecting a model to your systems and data. AI implementation is the whole change: choosing the workflow, integrating, measuring, training the team and running it afterwards. AI consulting stops at the recommendation. A quote that covers only integration leaves you to own the measuring and the running; ask which one you are buying.
How to choose an AI integration partner
The questions that separate a team that ships AI into production from one that ships demos:
- Will they test it on your own data before you commit to the build? A demo on clean sample data predicts nothing.
- What is the success criterion, in numbers, and who measures it?
- Where does a person review the output, and how does that review get lighter as accuracy is proven?
- Where does your data go, which model providers see it, and can it stay on infrastructure you control?
- Who runs it after launch, and who re-tests it when the model changes?
- Do you own the code and the prompts at the end?
Frequently asked questions
What are AI integration services?
AI integration services connect an AI model to the systems a business already runs, such as an ERP, a CRM, an inbox or a messaging channel, so that it does one specific job inside an existing workflow: reading documents into records, turning voice notes into orders, or letting an assistant update the CRM with a confirmation step.
How much do AI integration services cost?
At Reflekt Lab, an express scoping of one workflow costs $2,300 to $4,700, a full AI audit $7,000 to $14,000, and an audit plus a first workflow in production starts at $17,500. Running it afterwards starts around $470 per month, and model usage is a separate line in the quote.
What is the difference between AI integration and AI implementation?
AI integration is the technical work of connecting a model to your systems and data. AI implementation is the whole change: choosing the workflow, integrating, measuring results, training the team and running it afterwards. AI consulting stops at the recommendation.
How long does an AI integration project take?
A scoping takes days. A first workflow in production with a human review step typically takes six to ten weeks after the audit, depending mostly on how clean and accessible the data is.
Does our data go to OpenAI or another AI provider?
Only if you agree to it. The model and its provider are chosen with you, per workflow, and that choice is written into the scope. When data cannot leave your control, we run models on infrastructure you control, in the region you need.
Do you work with US companies?
Yes. We work in English, invoice in US dollars and schedule calls in your hours. A California industrial equipment company runs its shipping operations on a platform we built.
Pick one workflow to start with
A free 30-minute call. Bring the process that costs your team the most time, and leave with a view on whether AI is the right fix and what a first version would cost.
