Stop paying people to repeat the same computer work every day.
Dsign builds practical automation and AI systems around the software your business already uses — from simple chatbots to connected workflows and cloud AI linked to internal systems.
If staff do this repeatedly, it is worth investigating.
Start with one repetitive problem, not “we need AI”.
The best first project is usually the task that consumes time repeatedly and already follows a recognisable process.
People keep copying, sorting or retyping information.
Normal workflow automation may be enough. AI is added only where reasoning or language actually helps.
See What We Can Automate →The same questions are answered over and over.
A focused chatbot can answer from approved business information and capture enquiries.
See What We Can Automate →Our software does not work together.
APIs, databases, files, CRM, email and internal tools can be connected into one defined workflow where technically possible.
See What We Can Automate →Practical business workflows, not AI for the sake of AI.
These examples show the type of repetitive work worth investigating.
Enquiry handling
Read, classify, route and prepare responses from forms, email or other supported channels.
Reporting & analysis
Gather recurring data, summarise it and prepare useful business reports.
Marketing workflows
Generate post ideas, prepare content and connect defined approval or publishing steps.
Document processing
Extract repeat information from suitable documents and send it where it belongs.
Internal knowledge
Help staff search approved procedures, policies and business information.
System-to-system work
Move information between supported CRM, websites, databases, email and internal tools.
Assessment first. Technology second.
Sometimes AI is the wrong tool. Dsign first maps the repetitive work, systems, rules and exceptions, then recommends whether ordinary programming, automation, AI or a combination makes sense.
A website chatbot is a smaller first step than a custom workflow.
For businesses that mainly need customers to get fast answers from approved business information, a productised chatbot keeps the scope and price simple.
You supply your own supported AI API key, so variable model usage remains visible rather than hidden inside a marked-up package.
Configured around your business information.
- Website chatbot installation
- Basic business-information configuration
- Basic styling / branding
- Client supplies supported AI API key
- Basic testing and handover
- CRM, databases, actions and custom integrations quoted separately
Pricing follows the engineering work involved.
Number of systems, workflow steps, business rules, integrations, testing and reliability requirements all affect scope.
One defined repetitive workflow.
For a contained process with clear rules and limited system complexity.
- Workflow design
- Custom programming
- Basic API/integration work where needed
- Testing and error handling
- Handover
Multiple steps, rules or systems.
For workflows that need more programming, branches, logic or multiple systems working together.
- Multi-step workflow
- Business rules
- API/system connections
- AI where useful
- Testing and refinement
- Staff handover
AI connected to internal systems.
For AI that needs to work with internal software, files, databases, CRM or operational systems.
- Cloud AI model setup
- Local system integration
- Business logic and permissions
- Knowledge / data connection
- Testing and handover
Cloud, hybrid or fully local.
The model is only one part of the system. Deployment depends on the workflow, data, infrastructure and budget.
Cloud AI
The AI model runs in the cloud while Dsign connects it into the business systems and workflows it needs.
- Lower infrastructure cost
- Fastest to deploy
- Useful for most automations
- API/model usage billed separately
Hybrid AI
Combine selected local/internal workloads with cloud AI where both approaches add value.
- From R35,000+ implementation
- Hardware quoted separately
- Local + cloud working together
- Useful for internal data/workflows
Local AI
Run suitable AI models on hardware controlled by the business rather than relying entirely on cloud processing.
- Custom quote
- Dedicated hardware usually required
- Higher setup and maintenance cost
- Useful where local control matters
From annoying manual task to working automation.
The process starts with the business workflow, not a shopping list of AI tools.
Assess
Find the repetitive work and decide whether automation is worth it.
Design
Map the workflow, systems, data, approvals and business rules.
Build
Program the automation and connect the required systems.
Test
Validate normal cases, failures and important edge conditions.
Hand over
Set up users, document the process and support the team.
What businesses usually want to know before automating something important.
No. Normal programming and workflow automation are often cheaper and more reliable. AI is used where language, analysis or reasoning adds useful capability.
Yes, where the systems provide a supported way to connect. Cloud AI can also be integrated with local software, files, databases and internal systems through the implementation layer.
Even a focused workflow can require programming, authentication, APIs, business rules, error handling, testing and handover. The R2,500 chatbot is a separate productised setup with much tighter scope.
Yes. The official WhatsApp Business API can be added as an integration. Meta usage charges and any separate provider costs are billed separately and disclosed before setup; Dsign does not mark up Meta's standard usage charges.
Cloud uses hosted AI models, hybrid combines cloud intelligence with selected local systems or workloads, and local AI runs suitable models on hardware controlled by your business. The right choice depends on the workflow, data, budget and infrastructure.
The repetitive task, how often it happens, who currently does it and which software or systems are involved are enough to start.
Show us the manual work before you spend money on AI.
Tell us what your team repeats, how often it happens and which systems are involved. We can work out whether it is worth automating and what type of implementation makes sense.
Prefer a form?
Send the repetitive task and the systems involved. That is enough for the first assessment.