We design, deploy, and manage generative AI models tailored to your business needs. From chatbots and content generation to image synthesis and automation, our experts help you leverage the latest in AI innovation securely and ethically.
Enterprise Generative AI Strategy and Implementation
- Use-case discovery and ROI analysis
- Model selection, training, and evaluation
- Secure deployment and monitoring
- Governance, risk, and compliance alignment
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RAG, Fine‑Tuning, and Prompt Engineering
We implement retrieval‑augmented generation (RAG) with vector search, fine‑tune models on your domain data, and design safe prompts with validations, guardrails, and evaluation metrics.
Secure GenAI Deployment and Observability
We deploy behind private networks with data protection controls, auditing, and rate limiting. Observability includes prompt/response logging, drift detection, and human review workflows.
AI Productization and Experimentation
We run A/B experiments, manage feature flags, and measure task success, quality, and latency to continuously improve AI‑powered experiences.
Frequently Asked Questions
Which models and platforms do you support?
We work across open and hosted models (OpenAI, Anthropic, Azure OpenAI, open‑source) and deploy on AWS, Azure, and GCP.
How do you address security and governance?
We implement data classification, PII redaction, safe‑prompting, guardrails, audit logs, and human‑in‑the‑loop review.
Can you integrate AI into existing apps?
Yes. We add AI features to web, mobile, and backends via secure APIs and event‑driven workflows.
What is a typical timeline to MVP?
Discovery to MVP often completes in 3–6 weeks, depending on data readiness and scope.