Applied AI
Use AI where it can improve a defined process.
FAS evaluates and builds AI features inside existing business processes. Each engagement defines how results will be tested, reviewed, and supported before a larger rollout.
Services
What this service covers.
AI feasibility assessment
Review the task, available data, current cost, failure risk, and technical requirements before committing to implementation.
Internal search
Build search and question-answering tools that cite their sources and respect the access rules already applied to internal information.
Intake and document processing
Classify incoming requests, extract information, draft responses, summarize documents, and route items for human review.
AI features in software
Add model-based features to an application with logging, permissions, fallback behavior, and a defined support path.
Evaluation and monitoring
Test output quality, cost, speed, and failure cases against examples drawn from the process the system will support.
Access and human review
Set access rules, review points, fallback procedures, and documentation before the feature is placed into regular use.
Reasons to get in touch
A finished technical specification is not required.
- Staff spend significant time finding, comparing, extracting, or summarizing information.
- A repetitive process cannot be handled by fixed rules alone and still requires human judgment.
- An AI proposal needs a cost estimate, test plan, and decision about who will review the output.
- A prototype works in a demonstration but has not been tested with representative data or connected to the production process.
Starting an engagement
How the first decisions are made.
- 01
Define the task and baseline
Document how the task is handled today, what it costs, and which result would justify a change.
- 02
Test with real examples
Evaluate the approach with representative inputs, expected answers, and known difficult cases before connecting it to production.
- 03
Put it into operation
Connect the feature to the existing process, train the people who review it, and monitor cost and output quality after release.
Before building
AI is not always the right tool.
A database cleanup, rules-based automation, or a change to existing software may solve the problem with less cost and risk. An assessment should make that clear before implementation begins.
Start with the problem
Describe what is happening.
Share who is affected, what has already been tried, and any deadline or constraint. FAS will confirm whether the service is a fit and recommend a next step.
Start a conversation