AI SERVICES
Turn AI Strategy into Secure Execution.
Move from AI experimentation to practical business outcomes. Primenet AI Services combine AI engineering, security expertise, and operational discipline to help organizations design, deploy, and improve enterprise AI solutions.
We work alongside business leaders, developers, and security teams to connect investment priorities with usable systems, controlled deployments, and measurable results.
Enterprise AI with Business Purpose
Whether you are introducing a knowledge assistant, evaluating machine learning use cases, or automating security workflows, successful adoption requires more than a model.
Our approach connects business requirements, data readiness, application integration, governance, and operational ownership. Each engagement begins with a defined use case and agreed success measures.
How every engagement starts
01 Defined use case
A specific business problem with a clear owner.
02 Agreed success measures
Outcomes measured against an agreed baseline.
03 Data & integration readiness
Data, systems, and access reviewed up front.
04 Governance & ownership
Clear approvals, accountability, and handover.
What Our AI Services Deliver
Six practical service areas that take AI from idea to secure, supported production.
01
AI Strategy & Readiness
Identify practical AI opportunities, assess data and infrastructure readiness, and build a prioritized roadmap. Define expected value, implementation dependencies, risk ownership, and measures of success.
02
Generative AI & Enterprise Knowledge
Develop and integrate knowledge assistants and Generative AI workflows using approved enterprise data. Apply permission-aware retrieval, quality evaluations, and appropriate human review to support dependable use.
03
Machine Learning & Intelligent Automation
Assess and implement suitable ML use cases, such as anomaly detection, classification, forecasting, and workflow prioritization. Validate performance against representative data and business requirements before operational adoption.
04
MLOps & LLMOps Engineering
Establish repeatable processes for versioning, evaluation, deployment, monitoring, and rollback. Track relevant quality, latency, reliability, and cost measures as systems evolve.
05
AI Security Engineering
Integrate security requirements into applications, agent workflows, and delivery pipelines. Translate assessment findings into implemented controls and repeatable validation.
06
AI-Assisted Security Operations
Connect AI capabilities with security workflows to support triage, investigation, and controlled automation. Define where automation is appropriate and where analyst approval remains necessary.
FORWARD DEPLOYED ENGINEERS
Forward Deployed AI Security Engineers
Engineering Expertise, Embedded in Your Delivery.
A Forward Deployed Engineer (FDE) is a senior engineer embedded with your team—on-site or remotely—who owns delivery from design to production. Our Forward Deployed AI Security Engineers work directly with your teams to turn AI strategy and security findings into deployed improvements.
An FDE connects client requirements with implementation: understanding the business workflow, designing integrations, building controls, resolving findings, and preparing systems for operational handover.
Red Team Insight. Blue Team Defense. FDE Delivery.
Three disciplines working as one delivery team.
OFFENSIVE SECURITY SPECIALISTS
Red Team
Conduct authorized adversarial testing and challenge security assumptions.
Contribution: Evidence of weaknesses and realistic failure scenarios.
DEFENSIVE SECURITY SPECIALISTS
Blue Team
Build monitoring, detection, investigation, and response capabilities.
Contribution: Operational visibility and procedures for handling threats.
FORWARD DEPLOYED ENGINEER
FDE
Implement integrations, safeguards, application changes, and deployment improvements.
Contribution: Working solutions and a documented route to operation.
ALL DISCIPLINES TOGETHER
Joint Validation
Retest changes and review operational evidence.
Contribution: A repeatable feedback loop for ongoing improvement.
DELIVERY LOOP
One Continuous Improvement Cycle
Red team findings guide engineering changes. Blue team observations reveal operational gaps. The FDE connects both disciplines with application developers, infrastructure owners, and business stakeholders.
01
Assess
ALL TEAMS
Scope use cases, assets, and risks.
02
Test
RED TEAM
Challenge controls with attack simulation.
03
Implement
FDE
Build integrations and fix findings.
04
Monitor
BLUE TEAM
Detect and respond in operation.
05
Validate
JOINT REVIEW
Retest changes and review evidence.
↻ Each validation cycle feeds the next assessment, so protection keeps pace as models, data, and threats change.
What an FDE Engagement Delivers
The agreed engagement scope may include:
- ✓ A defined use case, architecture, and delivery backlog.
- ✓ An AI asset inventory and prioritized risk assessment.
- ✓ Application, API, identity, and security integrations.
- ✓ Evaluations and release checks for supported AI workflows.
- ✓ Monitoring dashboards and incident response playbooks.
- ✓ Deployment, rollback, and operational handover documentation.
- ✓ Knowledge transfer and an improvement roadmap.
Outcomes for Business Leaders
Metrics are selected for each engagement and measured against an agreed baseline.
Accelerate adoption
Establish a practical route from pilot to production.
Example measures: Time to deployment and user adoption.
Protect enterprise information
Strengthen access controls and data handling.
Example measures: Control coverage and validated exposure findings.
Improve productivity
Apply controlled automation to suitable workflows.
Example measures: Task completion time and analyst effort.
Manage operating costs
Make usage and infrastructure consumption visible.
Example measures: Cost per workflow or request.
Strengthen accountability
Define ownership, approvals, and operational records.
Example measures: Review completion and audit evidence availability.
Maintain quality and resilience
Introduce evaluations, monitoring, and recovery procedures.
Example measures: Evaluation results, error rates, and recovery performance.
Ready to Build Your Next AI Capability?
Work with Primenet AI Services to define a valuable use case, assess the risks, and establish a practical delivery plan.
or email sales@primenetbd.net