04 / AI & data
Put your business knowledge to work.
Help customers find answers and give your team a better way to process information. Devekko builds AI applications and the data foundations behind them using Cloudflare Workers AI.
Choose a task worth improving
Answer questions from your own information
Build an assistant over approved documents, product information, or internal guidance. Show the sources behind an answer and give users a useful next step when the information is missing.
Turn documents into reviewed records
Extract fields from incoming documents, check them against rules, and route exceptions to a person. Connect the reviewed result to the system your team uses.
Help people find the right item
Use semantic search to match the meaning of a question with relevant content or products. Keep access permissions and current source information attached to the result.
Assist a repeatable workflow
Classify requests, summarize material, or prepare a draft response. Define where the process can proceed automatically and where a person must review it.
Give the application dependable data
Useful AI starts with information your team can maintain. We identify the sources, connect the relevant systems, and make ownership and update rules explicit.
Data work can include pipelines, cleanup, shared definitions, quality checks, and reporting. It can also stand alone as a project when your immediate need is reliable information.
Built around Cloudflare Workers AI
Workers AI runs the selected models. Cloudflare Workers connects those models to your application and enforces access rules.
For document-based features, we choose managed AI Search or a custom retrieval approach around your requirements. Storage and background processing are added where the workflow needs them. AI Gateway gives the team a place to observe inference requests and apply controls.
The result is an application you can inspect and operate, with a clear path from its data sources to the task it performs.
Test a focused pilot before expanding
We define a task, representative examples, and success measures together. The pilot shows how the system handles ordinary requests, missing information, and difficult cases.
You can assess answer quality, review effort, response time, and operating cost before committing to a wider rollout. For document answers, we check source support. For extracted records, we check the fields against known examples.
A production scope adds the permissions, monitoring, failure handling, and maintenance process the application needs.
A few useful answers
Before we begin.
Do we need clean, organized data first?
We begin by assessing the sources you have. Data preparation can be part of the project, and the first pilot may use a small approved collection.
Can we use our existing tools and databases?
We assess their APIs, permissions, and data formats. The architecture can connect to existing systems where they meet the requirements.
Is our information used to train a model?
Cloudflare states that it does not use Customer Content processed by Workers AI to train AI models. We separately document application storage, logging, and retention before production use. Read Cloudflare’s data policy.
Will the AI always be right?
Model output can be wrong. The design uses source references, validation, evaluation, and human review appropriate to the task.
How much will it cost to run?
Running cost depends on the model, request volume, input and output size, storage, and indexing. We estimate the workload and measure the pilot before setting operating limits.
Can we start with data work alone?
Yes. Connecting sources, improving data quality, and building reporting can be a useful first project. Those foundations can support an AI feature later.
Your next project
Bring one workflow to the conversation
Describe the information people struggle to find or the task your team repeats. We can use it to define the first project.