Frequently asked questions

We utilize a variety of frontier models including Claude Opus 4.7 , and Gemini 3.5 Pro. The choice depends on the specific requirements of the project. For instance, we leverage Claude for complex reasoning and coding tasks, while Gemini is often preferred for massive context window requirements. Our team monitors benchmarks from platforms like LMSYS Chatbot Arena to stay updated on which models currently offer the best performance for specific programmatic tasks.

If you have a CTO, an agency serves as a force multiplier. A CTO often has the vision and system architecture skills but might be bottlenecked by execution capacity or specific domain gaps in AI/ML. Bringing in an agency allows your CTO to focus on high-level strategy and integration, while the agency handles the specialized implementation, data pipeline construction, or model fine-tuning. This hybrid model ensures your CTO retains technical oversight while the agency provides the necessary horsepower to meet aggressive development milestones.

Yes, we maintain full compliance with the General Data Protection Regulation (GDPR) for all data processing activities involving citizens of the European Union. This includes upholding individual rights such as the right to access, the right to rectification, and the right to erasure. We ensure that our data processing agreements explicitly outline the roles of data controller and data processor, providing our clients with the necessary legal framework to meet their own regulatory obligations when integrating AI solutions.

Our infrastructure utilizes secure, cloud based data centers with locations strictly determined by client requirements and regulatory needs. We offer options to localize data storage within specific geographical regions, such as the United States or the European Union, to ensure adherence to data sovereignty laws. Detailed records of server locations are provided to our clients as part of our standard onboarding transparency protocol, allowing compliance teams to map data flows accurately for their internal governance reports.

Hiring an external partner like VAiibe is superior when your team lacks the specific infrastructure to deploy AI solutions immediately. Agencies provide access to a pre-vetted team of specialists that would take months to recruit individually. This is ideal for startups needing to ship a minimum viable product or implement complex models without the overhead of full-time compensation packages. You get the benefit of established workflows and domain knowledge, which accelerates development timelines significantly compared to hiring and onboarding individual contributors.

Ownership depends entirely on the contractual agreement signed before work begins. Under United States copyright law, work made for hire agreements typically assign intellectual property rights to the hiring client. If your contract is silent on IP assignment, the agency might retain ownership of the underlying code, granting you only a limited license to use it. You should always insist on a clause that explicitly transfers all copyrights, patents, and trade secrets to your company upon payment.

Yes, we handle feature evolution as part of our ongoing maintenance. Because AI systems often require retraining or fine-tuning when new features are added, we treat these as iterative development cycles. We assess the impact of requested changes on existing model accuracy before implementation. Smaller feature requests are rolled into monthly maintenance retainers, while significant architecture changes are scoped as separate projects to ensure proper testing and validation.

We primarily serve the MENA and Europe regions. Our operational footprint is concentrated in these areas to allow for physical proximity where necessary and cultural alignment with the local business environment. This regional focus helps us understand specific market regulations, data sovereignty requirements, and local user behavior patterns, which are critical for deploying effective artificial intelligence solutions tailored to these markets.

VAiibe offers three primary pricing models to accommodate different business requirements. Project based pricing is used for defined scopes with clear deliverables and a fixed cost. Monthly retainers are available for ongoing support or advisory services, providing predictable costs over time. Time and materials contracts are used for flexible development work where the scope might evolve. We work with founders to determine which structure aligns best with their specific roadmap and budget constraints.

Not directly. The quote builder is a scoping tool: it captures your project brief in about 5 minutes (no price displayed). After that, we book a short call together where Oussema shares the tailored estimate based on what you submitted. This keeps the figure accurate, not a rough guess from a form.

Every project is different, so prices are personalized. The flow is simple: you fill the quote builder (about 5 minutes) to scope your needs, we get on a short call together, and I send you a tailored estimate right after. No commitment, no hidden fees.

Yes, maintenance is necessary to keep the chatbot functional and accurate. Monthly costs typically include API usage fees paid to model providers, cloud hosting expenses for vector databases or application servers, and ongoing performance monitoring. You should budget for periodic model updates or fine-tuning sessions to ensure the bot remains relevant to new information. While some platforms like VAiibe offer managed hosting to simplify these recurring costs, external API consumption remains a variable operational expense based on your monthly conversation volume.

A quote is built around three factors: the scope of the project (features and pages), the technical complexity (AI integration, automations, custom backend), and the timeline. The quote builder captures all of this upfront, then we go through it together on a short call before the final estimate is shared.

If a project scope changes significantly during the engagement, we utilize a formal change order process. This involves documenting the new requirements, assessing the impact on the existing timeline, and adjusting the budget accordingly. This prevents scope creep and ensures both parties agree on financial implications before new work begins. We prioritize open communication regarding these shifts to maintain budget control and delivery velocity.

Payments are split into milestones, usually a kickoff deposit followed by payments at each major delivery. Bank transfers and most international payment methods are accepted. The full schedule is agreed before any work starts.

Yes, projects start with a deposit (typically 30 to 40 percent of the total). It secures your slot in the schedule and covers the kickoff phase. The remaining balance is paid in milestones as we progress.

No. The quote covers everything we agreed on. If anything outside that scope comes up later (new features, extra integrations), we discuss and price it separately before any work happens. No surprises.

The cost for a custom AI chatbot spans a wide range based on scope. Simple internal tools might cost around 3,000 dollars. Mid-level implementations with third party integrations often fall between 3,000 and 5,000 dollars. Enterprise solutions requiring custom LLM fine tuning, complex database connectivity, and stringent security compliance can exceed 10,000 dollars. These figures cover discovery, architecture design, development, and basic quality assurance testing.

Four steps: kickoff (we align on goals, scope, and design direction), build (iterative sprints with regular previews), review (you test, give feedback, we polish), and launch (deployment, training if needed, handover). You have visibility at every step.

A shared channel (WhatsApp, Slack, or email, your choice) is used for daily messages, plus a weekly sync of about 30 minutes to review progress and decisions. Async first, calls when needed.

Revisions are built into the process: at each sprint or milestone, you give feedback and we iterate until the deliverable matches what we agreed. No artificial cap. Large scope changes (new features, redirection) are scoped separately.

It rarely happens because you see and validate at every step (design, build, polish). If something is off, it gets identified early and adjusted. The iterative process avoids the all or nothing final reveal.

Tunisia, but I work remotely with clients across Europe, North Africa, and the Middle East. Timezone overlap with Europe makes daily collaboration easy.

Three working languages: English, French, and Arabic (including Tunisian Darija). Project documentation, calls, and deliverables can be in any of them, or mixed if your team is multilingual.

Fully remote by default, that is how all my projects run today. On site visits remain possible in Tunisia or Europe for a kickoff or workshop, with travel costs covered by the client.

Yes, NDAs are standard, especially for AI projects, internal tools, or sensitive data. Send me yours or I can share a simple bilateral template. We sign before any sensitive info is shared.

Yes, professional AI agencies routinely sign Non Disclosure Agreements to protect your trade secrets, proprietary business logic, and sensitive data. Founders should ensure the NDA covers both the project development phase and any post project obligations. It is also standard practice to include non solicitation clauses to prevent the agency from poaching your internal staff or third party contractors during or after the development cycle.

We manage client data by implementing strict separation between internal development environments and client production systems. Information is encrypted both at rest and in transit using industry standard protocols such as AES 256. We operate under a zero trust security model, meaning every access request must be authenticated and authorized. Access to sensitive data is limited to essential personnel only, and we conduct regular security audits to identify and mitigate potential vulnerabilities within our pipeline.

Five main areas: web and app development (showcase sites, SaaS, mobile, dashboards), generative AI (chatbots, content generation, data analysis), automation (workflows, integrations), e-commerce and marketplaces, plus advisory work (SEO, audits, maintenance, tech consulting).

Yes. Cross platform (React Native or Flutter) is the default option because it ships faster and covers both stores. Native development stays available when a project really needs it. The right approach is discussed together during the scoping call.

Yes, AI integration is a core service. Common use cases: a chatbot trained on your data, content or document generation, search and recommendations, automation of repetitive tasks. We start with a quick audit to identify where AI brings real value, not just buzz.

Our post launch support focuses on model health and system stability. This includes real-time monitoring of model drift, infrastructure performance tracking, security patching, and regular evaluation of API latency. We also provide routine check-ins to review logs, analyze edge cases encountered by users, and verify that the AI remains within its intended operational bounds. For projects built via VAiibe, this often involves integrated monitoring dashboards to track performance over time.

Yes. You can either take a monthly retainer (covers updates, security patches, small evolutions, and priority support) or pay per intervention. We agree on what fits your usage during the launch phase.

Bugs related to what we built are fixed for free during the warranty window (typically 30 days after launch). After that, fixes are covered by the maintenance plan or billed per intervention. Either way, response is fast.

Yes. Every project includes a 30 day warranty starting from launch. Anything that does not behave as we agreed gets fixed at no cost during that window. Beyond that, maintenance plans take over.

Mainly Next.js and React on the frontend, Node and Firebase or custom backends on the server, Tailwind for styling, and tools like Genkit or OpenAI for AI features. Stack choice is always driven by what fits your project best, not by trend.

You do. Full ownership of the source code transfers to you at the end of the project (or at each milestone payment, depending on what we agree). Repositories, accounts, hosting credentials, all of it is handed over to you.

Yes. Recommended setups are Vercel, Firebase Hosting, or a custom VPS depending on the project. Hosting can be set up either under my account (with a small management fee) or under your own account with a full handover of the deployment process. Up to you.

For most professional applications, an AI integration timeline typically ranges from three to six months. Small scale projects involving basic API connections or simple automation scripts can be completed in four to eight weeks. However, projects requiring custom model training, complex data pipelines, or legacy system integration often extend beyond six months. Planning for discovery, data cleaning, model selection, development, and extensive testing phases is necessary to establish an accurate roadmap.

Yes, shipping an AI MVP in two weeks is possible if the scope is narrowly defined. To achieve this, you must limit the project to a single, well-documented data source and use pre-trained models rather than building from scratch. This approach focuses on solving one specific problem to validate utility before committing to a larger production system. Success in such a short window requires immediate access to clean data and existing cloud infrastructure.

The timeline depends entirely on the scope and complexity of your project. The precise duration is shared during our scoping call, once we have a clear picture of what you need. No empty guess upfront.

As soon as the quote is validated and the deposit received. If my schedule is busy, you are told upfront so we plan a realistic start date together. We never begin until you have full visibility on the schedule.

Yes, when my schedule allows it. Rush projects come with a tighter daily rhythm and a small rush fee on top of the standard quote. Best move: mention the deadline early so feasibility can be confirmed.