AI & Automation — Less busywork. Better answers.

Whichever fits the job and your data rules. Claude and OpenAI models for language tasks, open-source models hosted privately when data cannot leave your infrastructure, and speech and vision models where needed. Orchestration runs in code we write, or in n8n or Make when your team wants to see and edit the flows. We are not tied to one vendor.

Yes. Modern models handle Arabic well, and we tune prompts and examples for the way your customers actually write: Egyptian colloquial, Franco-Arabic in Latin letters, mixed Arabic and English in one message. Every assistant is tested on real conversations from your inbox before launch, and it responds in the language and register the customer used.

By grounding it. The assistant answers only from your approved content, products, policies and documents, cites where an answer came from internally, and hands over to a human when confidence is low or the question is out of scope. We test against a bank of real questions before launch, log every conversation and review the misses weekly in the first month.

Yes. WhatsApp Business API, website chat, Instagram and Messenger, email and SMS on the customer side; HubSpot, Zoho, Salesforce, Odoo, Google Sheets, Notion, Slack and most tools with an API on the business side. One assistant can serve several channels with one knowledge base, so answers stay consistent wherever the customer starts.

Your data is not used to train any model. We choose providers with enterprise terms that guarantee that, keep personal data minimal and encrypted, host on private infrastructure when your industry requires it, and set retention rules for conversation logs. Access is role-based and audited, and we document the whole data flow so you can answer your own compliance questions.

A customer assistant on one channel with a solid knowledge base launches in 3 to 5 weeks. A lead qualification or document extraction workflow takes 2 to 4 weeks. Larger internal tools and multi-step automations run 6 to 10 weeks. We start with a short discovery so the first thing we build is the one that saves the most time.

Two parts. A fixed project price for discovery, build, testing and launch, scoped by the number of flows, channels and integrations. Then a small monthly cost for model usage and hosting, which for most assistants is far less than one part-time salary, plus optional support. We give you the running cost estimate before you commit, not after.

It replaces the repetitive part of their day, not the people. The assistant handles the eighty percent of questions that have a known answer and hands the rest to a human with the context already gathered. Teams end up spending their time on sales conversations, complex cases and relationships, which is the work that needed humans in the first place.

Yes, and it should. Handover rules are designed with you: low confidence, angry customers, refunds, anything legal or medical, or simply a customer asking for a person. The conversation is passed with a summary and the collected details so nobody asks the customer to repeat themselves, and the human can hand it back when done.

Access to the questions your team answers today, from chat exports and email threads to your FAQ, a list of the tools you use, someone who knows the process well enough to say what the right answer is, and a decision-maker for the handover rules. If your documentation is messy, that is normal; organising it is part of the work.

We agree the metrics before building: first response time, percentage of conversations resolved without a human, leads qualified per week, hours saved on document handling, or cost per handled ticket. You get a dashboard with these numbers and a monthly review in the first quarter, and we tune prompts and flows based on what the data shows.

Yes. Assistants that search your policies and past projects, tools that draft proposals and reports from your templates, pipelines that summarise meetings and update the CRM, and copilots inside the software your team already uses. Internal tools are often the fastest win because the users are your own team and the data is already in your hands.

We build the model layer so it can be swapped. Prompts, knowledge and integrations live in your code and your accounts, and switching between Claude, OpenAI or a self-hosted model is a configuration change plus a round of testing, not a rebuild. Usage is monitored with alerts, so a price change shows up as a notification, not a surprise invoice.

Yes. Monthly support covers monitoring, reviewing missed questions, updating the knowledge base when products or policies change, model and dependency updates and small flow improvements. Most clients keep a light retainer, because an assistant that is reviewed monthly keeps getting better, while one left alone slowly drifts away from the business.