AI Integration for SMEs and Enterprises
Useful AI is AI plugged into your data and tools. Next Digits connects models and agents to your CRM, store, messaging and documents — with access control, traceability and human escalation.
Why integration matters more than the model
ChatGPT alone does not know your catalogue, customers or business rules. AI integration means wiring artificial intelligence into your systems so it acts in your context — not in a vacuum.
We design the architecture: data sources, APIs, access rights, logging, and what must never leave your environment.
What we connect
CRM and sales pipelines, Shopify and catalogue, email and WhatsApp, document bases, business tools and light ERPs. Every connection has a clear business goal: answer, qualify, extract, summarise or trigger an action.
Read, write and authorise are different permissions
An assistant that looks up a catalogue does not need the same rights as an agent that changes a customer record or triggers a refund. We separate access by action, limit available data and retain an audit trail for sensitive operations.
Flows that remain safe when the model is unsure
Every integration has a controlled exit: ask for clarification, hand over to a person or stop the workflow. An uncertain answer must never silently become an irreversible write in the CRM or ERP.
Who this is for
Companies that already have tools in place and want AI to work on top of them — not replace the whole stack. Ideal after a validated first use case, or when several systems must share the same assistant.
Security and governance
We document what leaves, where it goes, and under which conditions. Provider choices with non-reuse commitments, or models hosted with you when sensitivity requires it.
Moving from an AI demo to production integration
A demo performs well on a few selected examples. A production integration must handle missing fields, duplicates, languages, API downtime and requests outside its scope.
We build a test set from anonymised real cases, then track acceptable responses, critical failures and human escalations. Rollout starts with a limited scope before more actions are enabled.
- Representative test set before production
- Confidence thresholds and human approval for sensitive actions
- Usable logs for requests, decisions and errors
- Usage budget tracked by model, team or workflow
- Fallback to the manual process when an incident occurs
Examples of AI integration in Morocco
In retail, AI can retrieve product information and prepare a WhatsApp reply without sending it automatically. In sales, it can summarise a conversation, suggest the next action and draft a CRM record. In operations, it can classify a document or flag an anomaly before approval.
We favour assisted use cases where time saved is measurable and errors remain recoverable before fully autonomous agents. Autonomy follows reliability, not the other way round.
Our method
- 1
Map systems
Inventory of tools, available data and security constraints.
- 2
Define flows
What AI reads, writes, triggers — and what it is not allowed to do.
- 3
Integrate and test
Connectors, real-data test sets, quality criteria.
- 4
Go live
Progressive rollout, monitoring, tuning.
What we deliver
- AI integration architecture (data, API, rights)
- CRM / Shopify / messaging / document connectors
- Contextualised agents and assistants
- Guardrails, confidence thresholds, escalation
- Logs and quality tracking
- Documentation for IT / ops teams
AI integration budget
1–2 tool integration
From MAD 5,000
- Architecture and connectors
- 1 contextual assistant or agent
- Tests and documentation
Multi-tool stack
From MAD 12,000
- Multiple systems
- Governance and monitoring
- Training
Consulting & roadmap
From MAD 3,000
- Integration audit
- Use-case prioritisation
- Go / no-go recommendation
Scope depends on the number of systems and data sensitivity.
Frequently asked questions
What is AI integration?
Connecting AI models or agents to your business tools and data (CRM, ecommerce, messaging, documents) so they act in your context, with access rules and controls.
Can we keep our current tools?
Yes. AI integration adds to your stack via APIs, webhooks or automation platforms. We only replace a tool if it genuinely blocks the use case.
Will our data stay confidential?
Yes. We choose architecture by your requirements: contractual providers, isolation, or local hosting. Everything is documented.
How long for a first integration?
Often 2 to 6 weeks depending on the number of systems and API quality.
Connect AI to your tools
Free audit: we map your systems and identify priority AI integrations.