AI/ML Services
Generative AI
From GenAI strategy to production. We build large language model and multimodal solutions tailored to real enterprise workflows, with the guardrails to ship them safely.
What we deliver
Strong retrieval patterns, evaluation pipelines, and guardrails keep generative outputs accurate, grounded, and auditable across copilots, content, and decision support.
GenAI Strategy & Use Cases
- Identify high-leverage GenAI opportunities
- Build vs buy vs fine-tune decisions
- Prioritize by value, risk, and time to impact
- Define measurable success metrics
RAG & Knowledge Systems
- Retrieval-augmented generation over enterprise data
- Vector, hybrid, and graph-based retrieval
- Document parsing, chunking, and metadata strategies
- Permission-aware grounding and citations
Copilots & Multimodal Apps
- Domain copilots for analysts, engineers, and operators
- Text, image, audio, and document workflows
- Tool use, function calling, and structured outputs
- Seamless integration with existing enterprise UX
Evaluation & Guardrails
- Automated eval suites for accuracy and grounding
- Bias, toxicity, and PII detection
- Prompt injection and jailbreak resistance
- Cost, latency, and quality monitoring in production
GenAI without governance is a liability. With it, a multiplier.
We deploy generative AI tied to risk controls, evaluation, and human-in-the-loop oversight: productivity that scales without exposing the enterprise.
Source: McKinsey & Oxford, Delivering large-scale IT projects
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