Put AI to Work With ForwardDeployed AI Engineers
An AI demo can impress everyone and still leave daily work unchanged. SDI’s forward deployed AI engineers work alongside your team to connect models to real business data, build the right controls, and launch AI capabilities people can actually use.
Embedded AI Implementation
Why do promising AI pilots stallbefore employees can use them?
The hard part often begins after the prototype: incomplete data access, scattered systems, unclear approval rules, and no reliable way to measure results. SDI places AI engineering expertise close to your people and processes to solve those implementation challenges.
Move from a proof of concept to a practical release with clear owners, tested workflows, and a rollout your team understands.
SDI team augmentation starts at $3,999/month; ask about a forward deployed engineering engagement.
AI Data & Model Integration
Can AI work with the systems andknowledge your business already has?
Yes, when suitable access is available. Engineers can connect approved APIs, databases, and document collections; build retrieval-augmented generation (RAG); and design model-powered features around the information employees actually need.
Access controls, data boundaries, model selection, latency, and human review are addressed before sensitive features go live.
Practical AI in Production
Where can a forward deployed AIengineer create value first?
Start with one workflow where better answers, faster decisions, or fewer manual steps matter.
Knowledge Assistants
FIND TRUSTED ANSWERS
Give teams a searchable assistant grounded in approved documents, records, and knowledge sources, with citations where appropriate.
Decision Support
TURN DATA INTO ACTION
Add AI summaries, classifications, forecasts, or recommendations to existing operational tools and review steps.
Production AI Controls
OPERATE WITH CONFIDENCE
Set up evaluations, tracing, permission checks, fallback paths, and usage monitoring for live AI features.
From Pilot to Operations
How do you keep an AIfeature useful after launch?
SDI can establish test cases, review failure patterns, monitor costs and response quality, and refine prompts, retrieval, or model configurations as requirements change. Technologies may include Python, model APIs, vector search, RAG frameworks, and AI observability tools selected for your environment.
Your team defines the business outcome; our engineers help turn it into an operated, measurable capability—not another abandoned pilot.