A clear AI direction.
Define the use case, assess data readiness and compare model options against your needs. Establish evaluation criteria, deployment boundaries and a practical delivery roadmap.
Private AI model advisory & engineering
Private intelligence.
Built around
your business.
Your expertise deserves more than a generic model. We help you design, customize and deploy AI around your data, your workflows and the way your business works.
Model strategy · Custom LLMs · Forward-deployed engineering
Your business. Your AI.Architecture concept
01 / Your context
KnowledgeBusiness dataPolicies
Your custom AI modelGrounded · Adapted · Evaluated
Embedded in your workflows FDE delivery ↗
PRIVATE BY DESIGNHUMAN ACCOUNTABILITY
Business-specific intelligenceDeployment on your termsEngineering alongside your teamClear ownership & handover
What we do
From model decisions
to meaningful deployment.
We connect AI strategy with hands-on engineering, so the model you choose can become a system your team can actually use.
A model that knows your world.
Adapt large language models with the right combination of retrieval, fine-tuning and tools. Build around your knowledge, domain language and task requirements.
AI where work happens.
Integrate AI into the systems and processes your people already use. Design the human review, observability and operational handover needed to move beyond a prototype.
Forward-deployed engineering
Close to your team.
Closer to the problem.
FDE means our engineers work alongside your stakeholders and operators, turning real business constraints into working AI systems. We stay connected to the workflow, from discovery through rollout.
The deliverable is a usable system, with the knowledge to operate it.
Understand the work
Map the workflow, data access, risks and success criteria with the people who do the job.
Build against real examples
Create a model baseline and prototype, then evaluate quality with representative business tasks.
Integrate & validate
Connect the system, establish access controls and human review, and test it in the intended environment.
Deploy & transfer ownership
Roll out with agreed acceptance criteria, documentation, team enablement and a support plan.
Three ways to work together
The right depth.
For your next step.
Start with a focused pilot, build a production solution, or embed an FDE team for a broader AI program.
Standard
Discover & proveFor teams defining their AI opportunity and validating one focused use case.
Project-based quoteA focused advisory & pilot engagement
- Discovery and use-case prioritization
- Data and model readiness assessment
- Model shortlist and architecture proposal
- One scoped proof of concept
- Evaluation findings and delivery roadmap
- Technical handover session
Premium
Customize & deployFor teams ready to turn a validated use case into a custom AI solution.
Project-based quoteA custom model & production delivery engagement
- Standard discovery and planning
- Custom LLM architecture and adaptation
- RAG or fine-tuning, as appropriate
- Integration into an agreed workflow
- Quality, access and safety evaluations
- Deployment documentation and enablement
Superior
Embed & scaleFor organizations seeking an embedded engineering partner across a wider AI program.
Tailored engagementA dedicated FDE partnership
- Premium delivery capabilities
- Embedded FDE collaboration
- Multi-workflow and system integration
- Private deployment architecture planning
- Evaluation and improvement program
- Agreed support and operating cadence
Every engagement is scoped with you. Deliverables, timelines, deployment environment, support and pricing are confirmed in a proposal. Infrastructure and model-provider costs are quoted separately where applicable.
Designed around the job
Bring a business problem.
We’ll shape the AI approach.
Private knowledge assistants
Make internal knowledge useful with grounded answers and traceable sources.
Domain-specific copilots
Adapt AI to specialized terminology, tasks and decision-support workflows.
Document intelligence
Extract, classify and review information with defined human checkpoints.
Workflow automation
Connect models and tools to reduce repetitive work across existing systems.
Before we begin
A few useful answers.
Do we need to train a model from scratch?
Not necessarily. We start with the business task and compare suitable approaches, including existing models, retrieval-augmented generation, fine-tuning and tool integration. The goal is the right system for the task, not unnecessary model complexity.
What does “private AI” mean for our project?
We define data access, model hosting, retention and provider boundaries during discovery. Depending on your requirements, the architecture may use your cloud environment, an on-premises setup or a managed provider. Privacy controls and responsibilities are agreed for the selected deployment.
How is FDE different from a strategy engagement?
An advisory engagement helps define the direction. Forward-deployed engineering adds hands-on delivery alongside your team: implementing the solution, connecting it to workflows, validating it with users and preparing it for operation.
How are packages priced?
Pricing depends on scope, data readiness, integrations, deployment needs and the level of ongoing collaboration. Start with a conversation; we will define a proposal with deliverables, commercial terms and any third-party costs before work begins.
Who owns the solution and how is it handed over?
Ownership, licensing, access and third-party model terms are defined in the engagement agreement. We scope documentation, technical handover and team enablement so your team understands what is delivered and how to operate it.
Start a conversation
What should AI
do for your business?
Tell us about the workflow you want to improve. We’ll use your brief to discuss the right model approach and engagement.
info@cognarainc.com ↗