Embed intelligent assistants, search, and automation safely with robust guardrails and monitoring.
Production-ready LLM experiences tailored to your data and users.
Conversational assistants that understand your domain, processes, and tone.
Ground responses in your data with retrieval pipelines and vector search.
Connect LLMs to your systems for actions, insights, and automation.
Control outputs with policies, filters, and monitoring for safety and compliance.
Measure quality, latency, and cost to keep experiences reliable and efficient.
Provider-agnostic with focus on safety and performance.
OpenAI, Anthropic, Vertex AI, Azure OpenAI, open-source models where appropriate.
Vector stores (Pinecone, Weaviate), embeddings, chunking strategies, and metadata.
Moderation, red-teaming, prompt hardening, and content filters.
Tracing, logging, evaluation pipelines, latency/cost budgets, and dashboards.
Ship safely with clear checkpoints.
Define users, tasks, success metrics, and data sources.
Rapid prototyping with evaluation harnesses to validate quality and safety.
Implement retrieval, function calling, guardrails, and observability.
Rollout with cost/latency budgets, feedback loops, and ongoing evaluation.
How we keep LLM integrations reliable and safe.
Yes—we use retrieval, data access controls, and provider choices that align with your privacy requirements.
Safety is built in: prompt hardening, content filtering, policy checks, and human-in-the-loop where needed.
We’re provider-agnostic and pick models based on quality, latency, cost, and compliance for your use case.
Yes—automatic evals, human reviews, and feedback loops to track relevance, safety, latency, and cost.
Ready to transform your business with cutting-edge technology? Our team is here to help you navigate the digital landscape and achieve your goals.
Kathmandu, Bagmati, Nepal, 44600