OpenAI GPT.
Useful answers.
Built into your process.
We connect GPT to approved business information and define how it drafts replies, sorts requests and returns structured data.
Explore OpenAI GPT (opens in a new tab)
Why it helps
- Drafts replies and summaries from your instructions.
- Turns incoming requests into structured records.
- Customers can get a faster first response while your team reviews sensitive cases.
- Consistent outputs make follow-ups easier across channels.
Choose a task with a checkable result
GPT models can support tasks such as drafting, extracting information and classifying requests. We start with a narrow job and examples of acceptable output. A request to organise an enquiry into agreed fields is easier to evaluate than a broad promise to automate the whole sales process.
Provide the context the task needs
We define the instructions, source material and output format, then test a set of realistic inputs. The surrounding application needs to handle missing information and service failures. Any action that changes a customer record should also have a clear validation step.
Evaluate with your own examples
Fluent output can still be wrong. We compare results with expected answers, including ambiguous and incomplete requests, before deciding where human review is needed. The choice of model follows those results and the project’s response-time and cost requirements, rather than a general ranking.
Product reference: OpenAI text generation documentation. Our approach above describes how we plan and evaluate the work.
