AI Solutions & Engineering
Generative AI that works from your own material.
At a glance
- Best for
- Teams buried in documents, policies, tickets or records that take hours to search and draft
- Typical engagement
- Fixed-scope or ongoing, agreed to fit the work.
- Typical duration
- Varies by scope; agreed at the start of the engagement.
- Team
- Sized to the scope, drawn from our delivery team.
The problem
Where this costs you time.
Hours spent searching
Staff look for the right policy or record across many places.
Repetitive drafting
The same letters, summaries and reports get written from scratch.
Answers without sources
Generic tools invent answers that cannot be traced to your content.
What we do
Capabilities
Retrieval over your content
Answers drawn from your documents and records, with sources shown.
Drafting and summarisation
First drafts and summaries that people review before they are used.
Guardrails
Limits on what the tool answers, and when it says it does not know.
Approval workflows
A person confirms outputs that affect records, customers or money.
Access-aware answers
Each user sees only the content their role is allowed to see.
Quality measurement
Tracking of accuracy and feedback so the tool improves over time.
Benefits
What changes when this works.
Outcomes we design for. Measured results appear only after a client confirms them.
- Faster answers from your own content
- Drafts that start from the right facts
- Sources a reviewer can check
- Access that follows existing permissions
Process
How generative ai applications engagements run.
Stage 1
Discover and Diagnose
Business, workforce and compliance analysis.
Tech deliverablesProcess map, data-flow map, risk registerStage 2
Design and Align
Solution architecture, operating models, integration planning.
Tech deliverablesArchitecture, prototype, test planStage 3
Implement and Enable
Deployment, onboarding, system validation, change management.
Tech deliverablesBuild, integrate, test, trainStage 4
Govern and Optimize
Continuous compliance monitoring, reporting, automation and enhancement.
Tech deliverablesMonitor, support, improve
Technologies
Tools we would use.
Models
- Large language models
- Embeddings
- Vector search
- Speech-to-text
- Document understanding
Application
- Chat interfaces
- Document connectors
- Prompt management
- Retrieval pipelines
- Workflow integration
Controls
- Content filtering
- Usage logging
- Role-based access
- Human approval queues
- Source citation
Industries
Where this matters most.
Oil and gas
Assistants that search operating procedures and permits, with sources shown for each answer.
Pharmaceuticals
Drafting support for documentation, always reviewed before it leaves the team.
Chemicals and fertilizers
Shift handover and maintenance-log summaries built from the plant record.
Related
Where this connects.
- AI Product DevelopmentTurn an AI idea into a product that people can rely on.
- Problem and data assessment
- Model selection and evaluation
- Production-ready delivery
- Agentic AI SystemsSystems that carry out multi-step tasks, with clear limits and a person in charge.
- Task design with defined limits
- Tool and system integration
- Oversight and escalation paths
- Our platformStellar Core connects people, payroll and compliance.Explore Stellar Core
FAQ
Questions we hear.
Answers are drafted for review. Anything that needs a fact from Stellar is marked.
Have a business challenge worth solving?
Tell us what you're trying to fix. An engineer will reply, not a form robot.