Overview
We build practical AI systems — from intelligent assistants to document automation — with governance, monitoring, and human-in-the-loop controls.
Deploy AI That Delivers Real Business Value
We build practical AI systems — from intelligent assistants to document automation — with governance, monitoring, and human-in-the-loop controls.
Key Challenges We Solve
- Pilot projects stuck in proof-of-concept
- Hallucination and compliance risks with LLMs
- No monitoring for model drift
- Unclear ROI on AI investments
Industry Best Practices
Proven approaches built into the Treviox platform.
Use-case prioritization matrix
Score opportunities by feasibility, data readiness, and business impact before building.
Responsible AI guardrails
Implement prompt filtering, output validation, audit logs, and role-based access.
RAG over fine-tuning first
Retrieve domain knowledge from secure vector stores before costly model fine-tuning.
Continuous evaluation
Track accuracy, latency, cost per query, and user satisfaction in production dashboards.
Our Approach
We prototype in 2-week cycles, then harden the pipeline for scale with observability and cost controls.