Know what it may use
Approved collections, currency, ownership and access are designed before the interface.
AI assistants
Use AI to prepare and guide work without hiding its sources or limits.
GA Applications designs AI assistants that search approved knowledge, help interpret documents, draft guidance or prepare workflow actions. Every solution defines its sources, permissions, logging, retention, uncertainty, human review and escalation. The assistant supports an accountable person or process; it does not receive unlimited access or silently become the decision-maker.
Bounded requestWhat is the approved escalation route for a disputed result?
RequestRetrieveDraftReview
Draft with evidence
The assistant has prepared a response, but it is not an approved decision.
1Operations handbook / section 4.2approved source
2Service standard / reviewed 18 Julycheck currency
Pending review. No external action is available in this demonstration.
Approved sourcesVisible evidenceRole permissionsHuman reviewEvaluationDisable path
Useful because the job is bounded. Trustworthy because the boundaries are visible.
AI assistance belongs inside a designed operating process. It does not replace accountable people, authoritative records or competent professional judgement.
Let people inspect support
Citations, source context and uncertainty travel with the draft.
Keep decisions attributable
Permissions, review, escalation, logging and shutdown routes match consequence.
Six controlled applications, designed around real work.
Each route explains the source model, experience, workflow, governance and delivery needed for that particular use case.
Use case 01
Ai Crm Dashboards
Add controlled summarisation, classification and drafting to CRM and dashboard workflows with source links and human confirmation.Use case 02Controlled Knowledge Assistants
Help authorised users find and understand approved organisational knowledge with citations, permission-aware retrieval and human escalation.Use case 03Customer Guidance
Guide website and portal visitors through approved information, suitable next steps and human support without pretending to know more than the sources.Use case 04Document Intake Extraction
Receive documents, extract proposed fields and route uncertain information through human validation before records or workflows change.Use case 05Human Review Governance
Define ownership, approved use, evaluation, permissions, review, logging, escalation and shutdown controls for AI-assisted workflows.Use case 06Staff Guidance
Help staff find approved procedures, prepare checklists and escalate unusual situations without replacing supervision or competent judgement.01
Choose a bounded job and approved information set.
We define the user, question, sources, desired draft or guidance and the decisions the assistant must never make alone.
Useful fit
Repeated knowledge search, intake or drafting with verifiable context.
Poor fit
High-consequence judgement without reliable sources or review.
02
Show source boundaries and uncertainty in the interface.
Answers can cite retrieved material, distinguish source text from generated explanation and make correction or escalation easy.
Sources
Link to the approved item and relevant passage or record.
Limits
State when evidence is missing, conflicting or outside scope.
03
Place human review before consequential action.
The assistant may prepare a response, structured record or suggested next step, but authorised people confirm material communication or system changes.
Draft
Make generated content visibly editable and unapproved.
Action
Show destination, effect and evidence before confirmation.
04
Control access, logs, retention and model providers.
Project design covers user identity, source permissions, prompt and response handling, sensitive data, vendor terms, testing and incident response.
Least privilege
Retrieve only information the current user may access.
Logging
Retain enough for quality and investigation without collecting unnecessary content.
05
Prove usefulness and failure behaviour with a contained evaluation.
We build a representative question set, expected source behaviour, refusal cases and review rubric before expanding users or actions.
Evaluate
Test accuracy, citation, permission and escalation across normal and adversarial cases.
Operate
Assign content owners, review feedback, monitor drift and provide a disable path.
Questions worth answering
What teams ask before they commit.
Will an AI assistant always be accurate?
No. Models can misunderstand, omit or generate incorrect information. We reduce risk through approved sources, constrained tasks, citations, evaluation and human review, but do not promise perfect accuracy.
Can it access our private documents?
Only through a designed permission-aware connection and approved data handling. Access is not granted merely because a document exists in a connected system.
Can it take actions automatically?
Low-risk actions may be considered under explicit rules. Consequential changes, customer commitments and sensitive decisions should retain visible human approval.
Start with one bounded job
Assess where an assistant can help and where it should stop.
Bring a representative question, document or staff task. We will map sources, permissions, review and an evaluation path.