AI Workflow Intelligence and Governance Platform

Agentic Enterprise Orchestration System (AEOS) gives you a single, centralized layer to track how your AI agents behave, measure what they deliver, and govern their outputs across complex, multi-agent environments.

Built for production use, AEOS shows you what your AI agents are doing at every step of a workflow. You can evaluate output quality, review decision paths, and build a documented record of AI performance instead of relying on assumptions about what your systems are actually doing.

Objective

As AI adoption scales inside an enterprise, most teams hit the same wall: agents running production workflows, but no consistent way to see what those agents are doing, measure whether the output holds up, or prove the system stayed within policy.

AEOS closes that gap. The goal was not to add another dashboard on top of existing tools, but to turn AI agent activity into something you can measure, govern, and improve over time, the same way you manage any other part of the business.

The Problem for Enterprises Running AI Agents

No Visibility into Agent Decisions

Once an AI agent goes live, most teams lose sight of how it reached a decision. Standard application logs record that something ran, not why it ran that way, which makes errors hard to trace and harder to explain to compliance or leadership.

No Standard Way to Measure Performance

Enterprises running agents across multiple departments often have no consistent metric for comparing performance, tracking accuracy over time, or showing where AI is actually moving the needle and where it isn't.

Governance Gaps and Hallucination Risk

Without guardrails, agents can drift from policy, produce inconsistent outputs, or hallucinate in ways that go unnoticed until they cause a downstream problem.

Fragmented Monitoring Tools

Logs, performance data, and governance checks often live in separate systems, so no one has a single place to see the full picture of how AI is performing across the business.

Unclear ROI on AI Investment

Leadership teams pushing AI adoption frequently have no reliable way to show what agents are actually contributing, which makes it difficult to justify further investment or expansion.

Our Approach

Trigma's AI team built AEOS as a modular, scalable orchestration and analytics layer that sits on top of your existing multi-agent systems, rather than replacing them.

The platform captures every agent action as it happens: what decision was made, what data informed it, and what the outcome was, then turns that into structured, queryable insight instead of raw logs. Governance rules run alongside monitoring, so policy violations and hallucination risk surface in real time rather than after the fact.

The result is a centralized layer that combines AI visibility, governance, and performance intelligence into one platform, built to support enterprise-grade operations from day one.

Platform Features

AI Observability

Every agent decision and workflow step is captured in structured detail, not just a log line. You can see what an agent did and reconstruct why it did it.

Real-Time Monitoring

Agent activity streams live, so your team catches anomalies as they happen instead of finding them during a post-incident review.

AI Governance Layer

Guardrails keep agent outputs aligned with enterprise policy. Hallucination risk and policy drift get flagged before they turn into production problems.

Performance Tracking

Human and AI output are measured side by side, so you can point to exactly where AI is driving efficiency and where it isn't.

AI Workforce Analytics

AEOS treats AI agents as a measurable part of the workforce, tracking capacity and impact the same way you'd track any other operational resource.

Technology Stack

LLM Observability & Tracing

Langfuse

LLM Gateway / Routing

LiteLLM

Agent Orchestration

LangGraph

Governance / Guardrails

NeMo Guardrails

Backend

Node.js
Python

Frontend

Angular

Event Streaming

Kafka

Time-Series / Metrics Store

ClickHouse

Relational Database

PostgreSQL

Vector Database

Qdrant

Caching

Redis

Infrastructure

Kubernetes

Monitoring & Alerting

Prometheus
Grafana

Security & Access Control

Role-Based Access Control
OAuth2 / JWT

Cloud Storage

AWS S3

Results

AEOS turns AI agent activity into a structured, measurable record instead of a black box. Every action an agent takes is captured, analyzed, and surfaced as insight your team can act on.

For enterprises running AI at scale, that means real governance instead of guesswork, performance data you can actually use, and a clear line from AI investment to business outcome.

Results reported from an early AEOS enterprise deployment:



70%

faster root-cause analysis on AI workflow failures and production incidents.



55%

fewer governance and policy violations reaching downstream business processes.



43%

improvement in AI workflow efficiency through performance monitoring and optimization.



3.2x

greater visibility into AI operations, giving the team a clear read on agent contribution and business impact.