AI integration for apps and business workflows

Where AI can help

AI can help draft replies, sort requests or search documents. I first check whether it saves time on your task.

• Text work: draft descriptions, summarize messages and prepare material for human editing.
• Document search: answers grounded in available sources with links to the original information.
• Request processing: suggest categories, extract relevant details and hand them to the next step.
• In-app assistance: help users fill in or clarify a brief.

I test the use case with your data. For tasks with clear rules, I recommend conventional automation.

Connecting your data and applications

I integrate AI into an existing website, mobile app or internal system through available interfaces, keeping the feature in the environment your team already uses.

I configure data sources, result storage and access rights. Users only see information they are authorized to access.

If an interface is missing, adding it becomes part of the scope and budget. Document preparation, removing duplicates and keeping sources current also need to be included.

Validate the task before rollout

1. I select one task. Define inputs, expected outputs and where a person must decide.
2. I prepare evaluation cases. Include normal, incomplete, ambiguous and incorrect inputs.
3. I build a prototype. Check quality, response time and cost per request.
4. I evaluate the benefit. Compare with manual work, including time spent reviewing and correcting results.
5. I deploy the feature. Add permissions, limits, error monitoring and a fallback when the service is unavailable.

After testing, I summarize results, limitations and operating costs.

Output review and data handling

AI can produce inaccurate or unsupported results. The design needs to specify automated checks and human approval. For example, a proposed reply can remain a draft until a team member approves it.

I set separate permissions and approval steps for sending messages or changing records.

I select a provider based on your data requirements and document what information the service receives and stores.

Integration and operating costs

Initial costs cover defining the task, preparing data, connecting services, evaluation and application changes. Scope depends on source quality, available APIs and the degree of automation.

Operating costs include AI usage, data storage and retrieval, hosting and maintenance. Request volume, input and output length, and repeated attempts all matter.

I set usage limits and a way to monitor consumption. Current provider prices are checked when choosing the solution, and any savings are assessed alongside the cost of human review.

What I need for an initial proposal

• The task you want to speed up or simplify.
• A few anonymized examples of inputs and good results.
• Where the data is stored and which interfaces your system exposes.
• Approximate task volume and who will review outputs.
• Data-handling constraints and an indicative budget.

AI may be part of a broader project. If you are building a new product, I can combine this with mobile app development and build the backend and integrations.