Every engagement starts with a discovery call, usually in person if you are in Newcastle, Durham, or anywhere an hour off the A1.
People ask us what it is like to work with an AI software agency. What happens after you get in touch? How long does it take? What do you need from us?
Here is how we build AI software at Ayoob AI. Every project is different, but the process follows the same structure.
Phase 1: Discovery
Every project starts with understanding the problem. Not the technology. The problem.
We ask questions. What process are you trying to automate? What does it look like today? Who does it? How long does it take? What goes wrong? What systems are involved? What does success look like?
This phase usually takes one to two weeks. It includes:
- Stakeholder conversations. We talk to the people who do the work, not just the people who manage it. The person processing invoices every day knows things the operations director does not.
- Process mapping. We document the current process end to end. Every step, every decision point, every exception.
- Data review. We look at your data. What format is it in? Where does it live? How clean is it? How much of it is there?
- System audit. We map the systems involved. Databases, APIs, file shares, email, third-party tools. We identify integration points and constraints.
At the end of discovery, we produce a scope document. It describes what we will build, how it will work, what it will connect to, and what results to expect.
Phase 2: Design
With the scope agreed, we design the system.
Architecture. How the components fit together. Where the AI models sit. How data flows from input to output. What infrastructure is needed.
Data pipeline. How documents or data enter the system. How they are processed, validated, and stored. What happens to exceptions.
Integration design. How the AI system connects to your existing tools. Database connections, API integrations, file-based transfers, or other methods. We design for your specific systems.
User interface. If the system needs a human-facing interface (review queues, dashboards, configuration panels), we design it. Clean, functional, focused on the task.
Design takes one to two weeks. We share designs with your team for feedback before we start building.
Phase 3: Build
This is where the software gets built. Full code. No drag-and-drop. No low-code platforms.
We build in short cycles. Every one to two weeks, there is something to show. A working pipeline. An integration. A dashboard. Your team sees progress and gives feedback throughout.
AI model work. We select, configure, and test the AI models for your specific use case. We use a combination of commercial and open-source models depending on your requirements. If you need private deployment, we use open-source models that run on your infrastructure.
Pipeline development. The data processing pipeline that connects your inputs to your outputs. Ingestion, processing, validation, integration.
Integration. Connecting the AI system to your existing tools. We build and test each integration individually before connecting them.
Testing. We test against your real data. Not synthetic samples. Your actual documents, your actual workflows, your actual edge cases.
Build takes four to twelve weeks depending on complexity. Simple document processing pipelines are on the shorter end. Multi-system automation workflows are on the longer end.
Phase 4: Deployment
Deployment is not just putting software on a server. It is making sure it works in production.
Infrastructure setup. We deploy to your chosen environment. Your servers, your cloud, or a managed environment. We handle the infrastructure configuration, security, and monitoring.
Data migration. If the system needs historical data to work properly, we handle the migration. Clean, validated, ready to use.
User training. We train your team on how to use the system. Review interfaces, dashboards, exception handling, escalation procedures.
Go-live support. We monitor the system closely during the first weeks. We are available for immediate fixes and adjustments.
Phase 5: Support
AI systems are not "build it and forget it." They need monitoring, tuning, and occasional updates.
Performance monitoring. We track accuracy, speed, and exception rates. If performance drifts, we investigate and fix it.
Model updates. AI models improve over time. New models become available. We update when it makes sense for your use case.
System changes. When your business processes change, your source systems update, or you want to expand what the AI handles, we make the changes.
Support is ongoing. You have a team that knows your system and can respond quickly.
What we need from you
Building AI software is a partnership. We need a few things from your side:
- A clear problem. Not a technology wish list. A specific problem you want solved.
- Access to your data. Real documents, real records, real examples. We cannot build on hypothetical data.
- Access to your systems. Database access, API credentials, VPN access. Whatever we need to integrate.
- A point of contact. Someone on your team who can answer questions, give feedback, and make decisions.
- Time for feedback. Regular check-ins during build. Short sessions, but important.
How long does it take?
From first conversation to a live system:
- Simple automation (single document type, one integration): 6-8 weeks
- Standard project (multiple document types, several integrations): 8-14 weeks
- Complex system (multi-step automation, many integrations, private deployment): 14-20 weeks
These are realistic timelines based on projects we have delivered. We do not promise faster than we can deliver.
Getting started
If you have a process worth automating, start with a conversation. We will tell you honestly whether AI is the right solution and what it would take to build it. No pitch decks. No sales theatre. Just a clear assessment.
Book a discovery call and we will take it from there.
