Loading...
Menu
Loading...
Integrate artificial intelligence APIs (OpenAI, Claude, Google Vertex AI) into your existing applications. Robust architecture, controlled costs and Law 09-08 compliance.
AI APIs are powerful, but production integration demands much more than an HTTP call: rate limit management, multi-provider fallback strategies, per-token cost optimization, sensitive data security and real-time performance monitoring. We design abstraction layers that protect your application from API changes and let you switch between OpenAI, Claude or Vertex AI without modifying your business code. Every integration includes an intelligent caching system that reduces your costs by 30–50% on recurring requests, and guardrails to prevent any personal data leakage to models, in compliance with Law 09-08. We provide a consumption dashboard so you can manage your AI spend down to the dirham.
Automatically enrich your customer, product or prospect records with AI-extracted and structured data, categorization, scoring, named entity extraction.
Integrate text generation into your workflows: product descriptions, personalized email responses, document summaries, in French and Arabic, in your brand voice.
Automatically analyze customer reviews, social media comments and incoming emails, classify by topic, detect urgencies and route to the right department.
Related articles
An API call works fine in a demo, but production brings different constraints: rate limits, provider outages, token costs that drift. So we add an abstraction layer with rate limiting, automatic failover between OpenAI, Claude and Vertex AI, and a semantic cache that cuts the cost of recurring requests by 30 to 50 %. You then track latency and cost per request on a monitoring dashboard.
Yes, and that is precisely what the abstraction layer we design is for. It plugs into your application through REST or GraphQL APIs, in Node.js or Python, so your business code stays untouched, even if you later switch from OpenAI to Claude or Vertex AI. The first use cases usually come from flows already in place, since enriching customer records or classifying incoming emails builds on your existing data. The project starts with a scoping review of your current systems.
The amount depends on the functional scope, the number of systems to connect and your request volumes, because volumes are what weigh most on consumption. That is why we start with a scoping phase, which leads to a detailed proposal before any commitment. Every integration also ships with a consumption dashboard, so you can then manage your AI spend down to the dirham.
Yes, compliance with Law 09-08 is factored in from the design stage, because personal data should never leave for an external model as is. In practice, we anonymize data before any sending, encrypt exchanges in transit and put guardrails in place that block personal information from reaching OpenAI, Claude or Vertex AI. This setup is defined with you during scoping, based on the sensitivity of the data your application handles.
Booking a discovery for the coming weeks
Let's start.
Let's talk about your project. We respond within 24h and become partners who grow with you.