We build generative AI products that are useful in production, not just demos. Our Bangalore team delivers LLM-powered features, assistants, and workflow systems tied to measurable business impact.
Integrate GPT, Claude, and other LLMs into existing products with secure backend architecture.
Build retrieval-based applications that answer from your internal documentation and knowledge.
Implement agentic flows that call tools, execute steps, and escalate safely when needed.
Design prompt templates and structured outputs for consistency and downstream automation.
Add policy checks, scoring, and QA loops to improve reliability in production use cases.
Tune model routing and inference patterns to keep quality high and operating costs controlled.
We have shipped AI systems in live business environments with real operational constraints.
We choose model stacks based on your requirements, not vendor preference.
Local engineering collaboration with rapid iteration and transparent delivery.
Our implementation is tied to conversion, productivity, and support performance metrics.
Assistants grounded in internal docs for support, sales enablement, and internal operations.
Generate summaries, drafts, and decisions inside existing team workflows.
Search and answer systems over product, policy, and process knowledge bases.
Prioritize use cases and success metrics for generative AI implementation.
Design model, retrieval, and orchestration strategy for your product.
Implement features, integrations, and guardrails in iterative delivery cycles.
Deploy, measure quality and cost, then continuously tune system performance.
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Share your use case and we will define a practical roadmap to ship a production-ready GenAI feature set.