Generative AI & Agentic Systems
We create production-grade generative AI and agentic systems designed to reason, act, and operate reliably with enterprise guardrails and accountability.
The Problem We Solve
Many generative AI and agentic initiatives stall after early proof of concepts and can introduce unnecessary risk when pushed toward production.
Common challenges include:
- GenAI systems that hallucinate, drift, or behave unpredictably
- Assistants that lack context, traceability, or decision boundaries
- High operational cost and latency at scale
- Limited oversight, auditability, or compliance readiness
- No clear path from proof of concept to sustained production use
These challenges can result in escalating cloud and model usage costs, unstable systems that require constant fixes, delayed deployments, and growing exposure to regulatory risk.
What We Build
- Agentic AI workflows that break complex tasks into structured, multi-pass steps to improve accuracy and reliability
- Data-grounded generative AI with outputs that remain traceable to source systems for explainability and auditability
- Human-in-the-loop controls that enable review, escalation, and final accountability where risk or ambiguity exists
How It Operates in Production
Our generative AI and agentic systems operate through strategically orchestrated, multi-step workflows that combine planning, retrieval, tool execution and validation before delivering an output. Each action is grounded in enterprise data, constrained by policy guardrails, and logged for full traceability. This enables the systems to reason, act, and adapt reliably within real business workflows.
Sustained Operation & Support
We provide ongoing operational support to ensure generative AI and agentic systems perform as intended long after deployment.
Our ongoing support model includes:
- Monitoring of behavior, output quality, and drift
- Incident response and escalation for performance or accuracy issues
- Cost and latency optimization across infrastructure
- Iteration and tuning cycles informed by real usage data
- Compliance reviews, documentation, and audit support
- SLA-style ownership with defined responsibilities and accountability
Our Work: Proven Use Cases
These highlight how our team designs and operate generative AI and agentic systems that deliver measurable value in real production environments.
Real-Time AI Commentary at Scale
Partnered with the PGA TOUR and AWS to deliver real-time, generative AI commentary for tens of thousands of shots per tournament, transforming structured event data into contextual narratives at live event scale.
Agentic AI for Enterprise Asset Management Data
Implemented a multi-pass agentic AI workflow to automate the extraction of maintenance tasks, parts, and tools from complex technical publications for a defense asset management provider and reduced the manual effort by 98% while maintaining near-perfect precision.
Get Started with NLP Logix
We help organizations move generative AI and agentic projects from experimentation to dependable production systems. Our focus is on building agentic and generative AI solutions that operate safely, scale efficiently, and remain accountable long after launch.