Governed AI Systems for Production

The production-AI challenge

Building an AI Agent Is Easy. Trusting It in Production Is Hard.

Most teams can get an AI prototype working. Few can trust it in production. Autonomous agents need clear limits, verifiable output, and a record of what happened, and they need a reliable data and DevOps foundation underneath. NGDA builds that foundation and the governance layer together, so the system is trustworthy by design rather than by convention.

• Uncontrolled agent behaviour
• Missing audit trails
• Inconsistent verification
• Fragile automation
• Weak separation between execution and authorization
• Poor production reliability

The Agentic Workflow

Autonomous Execution. Human Authority.

The harness is how NGDA holds those two together: automation does the work, people approve each gate, and every stage carries a state a reader can see.

What NGDA builds

Engineering the Infrastructure Behind Intelligent Systems

Agentic AI & LLM Systems

Architecture and build of agent workflows and LLM applications: orchestration, tool and function calling, context management, multi-step handoffs, persisted run state, and human-in-the-loop approval gates.

• Multi-step handoffs
• Persisted run state
• Human-in-the-loop approval gates

Explore Agentic AI & LLM Systems

AI Governance & Verification

Policy-as-code guardrails that limit what an agent may do, executable acceptance criteria run in CI, conformance checks, audit trail and provenance design, and honest evaluation of LLM judges and metrics.

• Policy-as-code guardrails
• Conformance checks
• Audit trail and provenance design

Explore AI Governance & Verification

LLM Document Analysis

Pipelines that turn long documents (RFPs, specifications, requirements) into structured data and score them against criteria, with models routed per stage to balance cost and quality.

• Structured data
• Score them against criteria
• Models routed per stage

Explore LLM Document Analysis

Data Platform Engineering

PostgreSQL data models (star schemas, materialized views), ETL/ELT pipelines across enterprise systems, REST/SaaS integrations, and near-real-time telemetry pipelines.

• Star schemas
• ETL/ELT pipelines
• Near-real-time telemetry pipelines

Explore Data Platform Engineering

Analytics & Business Intelligence

Decision-grade dashboards and KPI reporting in Plotly Dash and Power BI, backed by validated data and machine learning where it adds value.

• Decision-grade dashboards
• KPI reporting
• Plotly Dash and Power BI

Explore Analytics & Business Intelligence

DevOps & Platform Engineering

Docker and Docker Compose, Linux (Ubuntu), Nginx, CI/CD with self-hosted runners, infrastructure-as-code, AWS, Windows-to-Linux container migrations, monitoring, and production incident diagnosis.

• Docker and Docker Compose
• CI/CD with self-hosted runners
• Infrastructure-as-code

Explore DevOps & Platform Engineering

Security & Assurance

Secure architecture, cybersecurity analysis, DoD certification and accreditation experience, LDAPS/Active Directory integration, and requirement traceability (ASPICE, IBM DOORS Next).

• Secure architecture
• Cybersecurity analysis
• Requirement traceability

Explore Security & Assurance

How NGDA works

From Architecture to Production. With Every Gate Verified.

1. Discover Map the workflow, data sources, constraints, and the decisions that must stay with people.
2. Specify Agree on written specifications with executable acceptance criteria, so “done” is testable.
3. Build Ship small, reviewed changes; automation does the work and people approve each gate.
4. Verify Tests, schema and contract validation, and conformance checks run in CI on every change.
5. Deploy & Operate Documentation, runbooks, and monitoring. Every production lesson becomes an enforced check, not a wiki note.

Proven engineering experience

Enterprise Experience. Production-Level Discipline.

Next-Generation Data Analytics LLC designs and builds governed AI systems and the data platforms beneath them. NGDA helps organizations move AI from prototype to production with human oversight, verifiable output, and a full audit trail, on a reliable data and DevOps foundation. NGDA is production-proven: experience running agentic systems, SaaS products, and enterprise data platforms in live production, including diagnosing real incidents. NGDA designs the system and builds it, from Python/Django services to containers, CI/CD, and cloud infrastructure.

ZoneVista

Production real estate analytics SaaS built and operated by NGDA. Flask application with 13 Plotly Dash dashboards over a PostgreSQL star schema, tiered subscription entitlements with row-level security, Stripe billing, self-hosted Docker/Nginx infrastructure, and SQL validation of every materialized view before changes ship.

zonevista.io

ngda-bidder

LLM document-analysis pipeline on the Anthropic API that extracts structured requirements from RFPs and scores them against evaluation criteria, routing models per stage for cost and quality.

Industries

Where This Work Applies

These are areas of expertise, not a client list: NGDA names no client and publishes no customer.

Automotive and autonomous mobility

NGDA serves regulated automotive work: ADAS and ASPICE requirement traceability.

Aerospace and defense

NGDA serves aerospace/defense work: certification and accreditation.

Enterprise software and technology

Agent workflows and LLM applications, on the containers, CI/CD and cloud infrastructure beneath them.

Data-intensive commercial organizations

PostgreSQL star schemas and materialized views, ETL/ELT pipelines, and near-real-time telemetry.

Regulated and mission-critical environments

Policy-as-code limits on agent actions, human approval gates, and a full audit trail from intent to merged change.