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AI & intelligent workflows / LLM application development
Useful intelligence. Visible limits.
Language-model applications can help people work through unstructured information. Their usefulness depends on the surrounding product, evidence, evaluation, and failure handling.
Talk through your project
Technology in focusLLMEvidence / Evaluation / Control
A connected engineering approach
- 01Experience
People, tasks, accessibility
- 02Application
Components, logic, integrations
- 03Foundation
Data, operations, maintenance
The architecture follows your product requirements.
01 / Where it fits
Built around
a real use case.
Assisted workflows
Draft material that a person can inspect and revise.
Conversational products
Answer bounded questions within a defined context.
02 / Architecture
The decisions
behind the build.
A sound foundation
Set data boundaries, retrieval rules, output contracts, and escalation paths. Record model and prompt versions, and make uncertainty visible in the interface.
The tradeoff to consider
Model output is probabilistic. A fluent answer is not proof of accuracy, and sensitive decisions may require direct human review.
03 / Delivery & care
Make it work.
Keep it dependable.
Quality in the details
Build representative evaluation sets, test adversarial inputs, and track groundedness, latency, and cost. Review behavior when models or dependencies fail.
Understand
Review the users, existing systems, constraints, and definition of success.
Shape
Document the architecture, interfaces, risks, and delivery scope.
Build & validate
Review working increments against real use cases and failure conditions.
Handover & evolve
Prepare operating guidance, ownership, and a practical maintenance plan.
04 / A few useful questions
Before you begin.
Is LLM the right choice for my project?
Model output is probabilistic. A fluent answer is not proof of accuracy, and sensitive decisions may require direct human review.
Can we improve an existing application?
Start with a code and architecture review. The useful outcome is a clear decision about what to keep, improve, or replace, with the dependencies and delivery risks made explicit.
How are scope and cost determined?
The estimate depends on the workflows, integrations, platform requirements, and quality expectations. A focused discovery phase can reduce uncertainty before committing to the full build.
What happens after launch?
Agree on source ownership, documentation, monitoring, support responsibilities, and a maintenance plan as part of the engagement.
Something in mind?
Let's buildwhat's next.
A new website. A better product. A bigger possibility.It starts with a conversation.