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Solutions / GA Applications

Solution / Assisted knowledge

Help people work from approved knowledge without disguising uncertainty.

A knowledge and AI assistance solution helps authorised users search approved material, receive source-linked summaries and prepare drafts within defined boundaries. GA Applications designs the content pipeline, permissions, prompts, review controls and feedback path so assistance remains traceable and people can verify important statements before acting or publishing.

Problemone recurring constraint
Flowpeople, records and hand-offs
Outcomeobservable working change
Why it matters

Source register

Identify approved documents, owners, audiences, review dates and confidentiality.

CHAPTER 01

Prepare the knowledge before adding an assistant.

Conflicting, stale or inaccessible source material produces unreliable assistance regardless of model quality.

01.1

Source register

Identify approved documents, owners, audiences, review dates and confidentiality.

01.2

Content structure

Break material into meaningful sections with stable identity and useful metadata.

01.3

Lifecycle

Remove superseded material from active retrieval while preserving required records appropriately.

CHAPTER 02

Define tasks the assistant may perform and how it must show its basis.

Search, summarisation, drafting and extraction have different risks and acceptance tests.

02.1

Grounded answer

Return source references and acknowledge when approved material does not answer the question.

02.2

Drafting boundary

Label generated content as a draft and retain review for commitments or external publication.

02.3

Structured extraction

Validate extracted fields and route uncertainty rather than filling gaps with invented values.

CHAPTER 03

Keep permission, review and improvement visible.

The assistant should respect the user's authorised source set and create a practical path for correction and escalation.

03.1

Access boundary

Filter retrieval and actions according to the same approved identity and record permissions.

03.2

Human decision

Name the person responsible for checking important output before use.

03.3

Evaluation

Test representative questions, unsupported requests, source conflicts and harmful failure modes before release.

Questions worth resolving

What to clarify before committing.

Will the assistant always be correct?
No. AI output can be incomplete or wrong. Source grounding, clear uncertainty, representative evaluation and human review are required for important use.
Can it use private company documents?
Potentially, under an agreed architecture that covers access, provider terms, retention, logging and the sensitivity of the material.
Can the assistant take actions in other systems?
It can prepare or trigger approved actions, but higher-risk changes should require confirmation, validation and a traceable result.

Bring the real problem

Choose one knowledge task and its approved sources.

Bring representative documents, user roles and the decision that follows the answer. We can scope a controlled assistance pilot.