AI Agency in Morocco
Next Digits applies artificial intelligence where it genuinely saves time: chatbots, AI agents, sorting and data extraction, assisted replies. AI connected to your tools and your data — a means to run your operations better, not a gimmick.
Useful AI, connected to your business
Generic AI impresses in a demo and disappoints in production, for a simple reason: it knows neither your catalogue, nor your customers, nor your business rules. It produces plausible answers rather than correct ones — which is worse than no answer when a customer is waiting.
The real lever is AI wired into your data: CRM, Shopify store, email, WhatsApp, internal documents. We build assistants and agents that work on YOUR information, with guardrails and human control wherever an error is expensive.
The use cases that survive production
After around fifty projects, these are the ones that produce measurable gains for a Moroccan business — and the ones we usually advise against starting with.
Support and sales chatbot
A chatbot connected to your catalogue, FAQs and delivery times answers repetitive questions properly: availability, price, order tracking, returns policy. The gain is immediate at high volume, and escalation to a human stays available at any point.
Qualifying incoming requests
Automatically sorting what arrives by form, email or WhatsApp: sales enquiry, complaint, technical question, spam. Each message goes to the right person with a summary, instead of piling up in a shared inbox.
Extracting data from documents
Supplier invoices, purchase orders, scanned forms: the AI reads the document, extracts the useful fields and pushes them into your system. Often the clearest return on investment, because it replaces entirely manual data entry.
Summarising and drafting assistance
Summarising a long customer thread before handing it over, preparing a draft reply a human approves, generating product descriptions from specifications. The AI prepares, the person decides.
What we advise against starting with
An agent expected to make financial decisions alone, or to answer unsupervised on a subject where an error creates liability. Those projects rarely fail in a demo and almost always fail in production.
AI or conventional automation?
The question comes up in every project and deserves an honest answer, because it changes the budget by a factor of five.
Conventional automation follows fixed rules: cheaper, faster, perfectly predictable, and never wrong on a case it knows how to handle. If your process can be written as rules, AI adds nothing — it adds cost and uncertainty.
AI becomes relevant as soon as you need to understand free text, handle ambiguous cases or read an unstructured document. In practice the best systems combine both: AI interprets and decides, automation executes reliably.
Your data stays your data
It is the first question our clients ask, and a fair one. We choose the architecture according to your requirements: providers that commit to not reusing your data, processing on controlled infrastructure, or models hosted with you where sensitivity justifies it.
We document what leaves your system, where it goes, and what does not leave. You need to be able to answer that question in front of a client or an auditor.
From use case to deployment, without the hype
We start from a measurable problem, not a wish to 'add AI'. We scope the use case, test on your real data, measure the quality achieved, then deploy only if the results justify it — and we tell you when they do not.
Based in Casablanca, we support SMEs and companies across Morocco with pragmatic AI integration.
Our method
- 1
Start from a measurable problem
What volume, what time spent, what cost today. Without that starting figure it is impossible to say whether the project succeeded.
- 2
Scope the use case
We define what the AI must handle, what it must refuse to handle, and where a human takes back control.
- 3
Test on your real data
A prototype evaluated on your own cases, not on cherry-picked examples. This is the stage where many AI projects should stop — and where we will say so.
- 4
Deploy with guardrails
Progressive rollout, monitoring, confidence thresholds and escalation to a human whenever the system is unsure.
- 5
Measure and adjust
Tracking real quality over time. A model that worked at launch can drift as your data changes.
What we deliver
- Support and sales AI chatbots (catalogue, FAQ, orders)
- AI agents connected to your tools (CRM, Shopify, email, WhatsApp)
- Document extraction and classification (invoices, forms)
- Automatic qualification and routing of incoming requests
- AI-assisted automation (sorting, summarising, replies)
- Custom AI integration via API, with guardrails
- Quality measurement before and after deployment
- Team training on usage and on limits
AI project budget
First use case
From MAD 3,000
- Scoping of one precise use case
- Prototype tested on your data
- Measurement of achieved quality
- Honest go / no-go recommendation
- Delivered in 2-4 weeks
Agent in production
From MAD 9,000
- Agent connected to your tools
- Guardrails and human escalation
- Integration into your workflows
- Monitoring and quality dashboard
- Team training
Ongoing support
Monthly quote
- Quality tracking over time
- Adjustments and retraining
- New use cases
- Monitoring of available models
- Priority support
On top of these figures sits the usage cost of the AI models themselves, billed by consumption by the provider. It is usually modest against the time saved, and we estimate it during scoping so there are no surprises.
Frequently asked questions
Move to AI that earns its place
Free audit: we identify the AI use cases with real return in your business — and the ones that are not worth it.