Search internal and external guidance · Compare new requirements with current procedures · Prepare evidence checklists · Draft internal or customer briefings
Private AI & knowledge systems
Turn company knowledge into a working system.
Context / Consequence helps organisations identify where AI can reduce repetitive knowledge work, improve access to internal information and support more consistent decisions. We lead the workflow, knowledge and governance design, then build or coordinate a focused assistant around approved sources, permissions and human review.
Start with the job the system needs to do—not the model name.
The distinction
Organisation-specific does not mean training a new model.
Most organisations do not need to train a language model from scratch. They need a carefully designed system that can retrieve the right approved information, provide it to a suitable model and return a useful answer with visible sources and clear limits.
The result feels organisation-specific because it understands the relevant documents, terminology, templates and workflows. The underlying model and hosting approach can then be selected according to performance, privacy, cost and infrastructure requirements.
01Approved knowledge→
02Retrieval and permissions→
03Suitable language model→
04Cited answer or draft→
05Human review
What it can support
Useful knowledge work. Visible human control.
The initial focus is read, retrieve, compare, summarise and draft. Higher-risk actions or decisions remain subject to explicit human control.
Deployment choices
Privacy is an architecture decision.
Different organisations need different levels of control. Context / Consequence defines the requirement first and recommends an appropriate deployment route.
A claim that information does not leave the organisation is only made where every relevant component—including model inference, document processing, embeddings, logs, analytics and backups—has been designed accordingly.
Engagement options
One useful workflow. A proportionate starting point.
Begin with a decision-ready review, a focused working pilot or the controlled expansion of a validated system.
01Approximately one week
AI Opportunity Review
Identify where private AI could create useful and defensible value before committing to implementation.
INCLUDES
- Interviews with relevant team members
- Workflow and information-source mapping
- Prioritisation of potential use cases
- Data, security and governance considerations
- Recommended architecture and pilot scope
- Indicative implementation cost and benefits case
OUTCOME
Discuss an opportunity review A decision-ready recommendation showing what to build, what not to build and why.
02Approximately three to four weeks
Private Knowledge Assistant Pilot
Build and test a focused assistant for one team, knowledge collection or repeatable workflow.
INCLUDES
- One prioritised use case
- Approved source collection
- Knowledge retrieval and source citations
- Role-appropriate access
- Defined prompts and output templates
- Human approval points
- User testing and refinement
- Basic staff guidance
- Pilot evaluation against agreed measures
OUTCOME
Discuss a pilot A working pilot and evidence for whether it should be expanded.
03Scoped to the organisation
Managed Private AI System
Extend a validated pilot across additional information sources, users and workflows.
INCLUDES
- SharePoint or Google Drive connections
- Permission-aware retrieval
- Private-cloud or self-hosted deployment
- Audit and usage reporting
- Multiple workflow interfaces
- Governance and acceptable-use documentation
- Staff training
- Ongoing knowledge-base management
- Performance monitoring and improvement
OUTCOME
Scope an implementation A managed system with an agreed plan for support, knowledge maintenance and continuous improvement.
Specialist infrastructure, cybersecurity and engineering partners are brought into delivery where the technical or risk profile requires them. Context & Consequence remains responsible for the business problem, workflow design, knowledge structure, implementation brief, testing and client delivery.
Delivery methodology
From the job to a governed system.
Guardrails
Useful systems need visible limits.
Local hosting alone does not resolve accuracy, data-protection or governance requirements. The system must still be designed and operated with appropriate accountability, security and oversight.
- 01Approved-source boundaries
- 02Source links or citations
- 03Role-based access
- 04Defined retention and logging
- 05Human approval for sensitive outputs
- 06Testing against representative questions
- 07Clear escalation when the system lacks sufficient evidence
- 08Version and knowledge-base maintenance
Initial relevance
Where specialist knowledge meets repeated work.
The strongest use cases normally sit where organisations hold substantial specialist knowledge, operate in a changing policy environment and repeatedly convert complex information into briefings, proposals, procedures or customer communications.
01Housing and property technology
02Building safety and construction
03Security and venue operations
04Membership bodies and trade associations
05Policy, communications and professional-services firms
06Heritage and cultural organisations
07Regulated technology and service businesses
Frequently asked questions
Clear architecture. No model theatre.
Start with one workflow
What useful work should the system make easier?
You do not need a finished technical specification or a preferred model. Bring the repetitive task, difficult knowledge problem or sensitive workflow and we can determine whether a private AI system is the right response.