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EcoSec WorX

Agentic AI Engineering for the Real World

Build Your Agentic AI Stack. Faster.

From strategy and architecture to production deployment, EcoSec WorX helps organizations build secure, context-aware Agentic AI systems without starting from zero.

Cloud agnostic by design

  • AWS
  • Microsoft Azure
  • Google Cloud
Agentic AI reference architectureOperational signals flow into a supervisor agent that draws on an Operational Semantic Model and a knowledge layer, delegates to specialist agents, calls tools through an approval gate, and writes every step to an evidence record.SIGNALSSPECIALISTStelemetryeventsalertslogsAPIsOSMoperational contextSupervisor agentplan · delegate · verifyKnowledgeRAG · graph · SOPsDiagnoseCorrelateRemediateTools · MCPApproval gateEVIDENCE RECORD · run_7f3a · 14:02:11Zobserved → context → decision → approval → tool call → change
Reference pattern. Your business logic stays custom — the plumbing doesn't have to be.
What we do
Build production Agentic AI systems
How it starts
Architecture Sprint → Go / No-Go
Who owns it
You own your custom work
After launch
Support, maintenance, monitoring

The executive problem

Everyone Wants AI. Few Organizations Know What to Build First.

Most organizations have run an experiment. Far fewer have a production system that integrates with real applications, APIs, data and telemetry — with the security, governance and evidence an enterprise needs. The gap between the two is architecture, not enthusiasm.

  • Where should we start?
  • Which use cases are actually worth building?
  • Can agents safely touch our operational systems?
  • Who owns what gets built?
ExperimentationProduction Agentic AI
  • A demo that answers questionsA system that acts on your operations
  • Prompts and documentsLive signals, context and governed tools
  • One clever modelSupervised agents with bounded authority
  • "It seemed to work"Evidence of what it observed, decided and did

Our differentiator

We Don't Start With a Blank Screen.

Your business logic is custom. The plumbing doesn't have to be. EcoSec WorX brings existing architectural patterns and reusable Agentic AI building blocks, so engagement time goes into what makes your system unique — not into reinventing orchestration, guardrails and audit trails.

Agents & Orchestration

  • Supervisor agents
  • Specialist agents
  • Multi-agent orchestration
  • Workflow engines
  • Memory & context

Knowledge & Context

  • Retrieval-Augmented Generation
  • Knowledge bases
  • Knowledge graphs
  • OSM context models

Integration & Signals

  • Tool integrations
  • APIs
  • MCP integrations
  • Event-driven architecture
  • Telemetry ingestion
  • Operational signals

Security & Governance

  • Identity & authorization
  • Guardrails
  • Human-in-the-loop controls
  • Policy enforcement
  • Security controls

Evidence & Observability

  • Audit trails
  • Evidence collection
  • Agent activity logging
  • Observability

Platform & Operations

  • Cloud infrastructure patterns
  • AIOps components
  • Operational dashboards

Custom layer

Your application and business logic — built specifically for your organization, on top of proven components.

Engagement model

Crawl. Walk. Run.

Risk is controlled in stages. Every engagement begins with an Agentic AI Architecture Sprint that ends in an explicit Go / No-Go decision — before any major investment. Our job is not to convince you to build AI. Sometimes the right answer is "don't build it yet."

Start With an Architecture Sprint
  1. Stage 1

    Crawl

    Discover & Architect

    A focused sprint to decide whether the opportunity is worth pursuing — before major investment.

    Offer

    Agentic AI Architecture Sprint

    Deliverables

    • Prioritized use cases
    • Reference & agent architecture
    • OSM / context model
    • Knowledge & integration strategy
    • Cloud recommendation
    Go / No-Go Decision
  2. Stage 2

    Walk

    Build the MVP

    If the Sprint produces a GO, we build a working system that demonstrates measurable operational value before scaling.

    Outcome

    Working Agentic AI MVP

    Typical components

    • Supervisor agent
    • Specialist agents
    • Selected integrations
    • Knowledge base
    • Telemetry & OSM
    Validated Value
  3. Stage 3

    Run

    Production Agentic Operations

    Validated systems move into production with the architecture, hardening and support that enterprise operations require.

    Outcome

    Production deployment & operations

    Typical components

    • Production architecture
    • High availability & scalability
    • Multi-agent & multi-tenant systems
    • Cybersecurity hardening
    • Enterprise integrations
    Operate & Improve

Context before intelligence

AI Without Context Is of Limited Value.

A model can reason. An operational system also needs to understand the environment it operates in. Our Operational Semantic Model (OSM) gives agents machine-readable context: what something is, where it is, what it connects to, what state it's in, who owns it, which policies apply and which actions are appropriate.

An LLM gives an agent intelligence.

An OSM gives it operational understanding.

  • Assets
  • Devices
  • People
  • Customers
  • Locations
  • Systems
  • Relationships
  • Events
  • Policies
  • Roles
  • Procedures
  • Historical conditions
  • Operational states
  • Security constraints
Operational Semantic Model exampleA single asset, GW-07, connected to its type, location, network, current state, owner, governing policy and permitted actions.is aEdge gatewaylocated atSite North · Rack 4connected toVLAN 30 · 42 devicesstateDegraded since 13:48owned byField Ops · on-callgoverned byChange-window policypermittedRestart w/ approvalGW-07asset

Telemetry & operational signals

Give Your AI Agents Eyes and Ears.

Agentic AI shouldn't operate on documents and prompts alone. We connect agents to the signals that describe what is actually happening — telemetry, events, alerts, logs, sensors, infrastructure metrics, security events and network data — so they can understand a situation and determine what action should occur.

SignalsWhat is happening
ContextWhat it means here
KnowledgeWhat we have learned
ReasoningWhat should happen
ToolsWhat can be done
Agentic OperationsUnderstand, decide, act — with evidence

KnowledgeOps

Turn Tribal Knowledge Into Operational Intelligence.

Capture what your best people know before it walks out the door. Much of an organization's most valuable operating knowledge lives in engineers, technicians, operators and subject matter experts — not in documentation. KnowledgeOps captures, organizes and operationalizes that expertise so agents and future employees can use it.

Where it lives

People

  • Engineers
  • Technicians
  • Operators
  • Executives
  • Support teams
  • Subject matter experts
Capture

Sources & methods

  • Expert interviews
  • Conversational capture
  • SOPs & procedures
  • Incident history
  • Troubleshooting notes
  • Documents
  • Tickets
  • Logs
Structure

Operational knowledge

  • Knowledge base
  • Vector search
  • Knowledge graph
  • OSM context
Use

Who benefits

  • AI agents
  • New employees
  • Operators on shift
  • Incident responders

Cybersecurity, built in

When AI Gets the Keys, Security Changes.

Once agents can act, authority becomes attack surface. Security is a foundational design principle in every EcoSec WorX architecture — never an add-on after the system is built.

Authority agents may hold

  • Query databases
  • Call APIs
  • Modify systems
  • Create tickets
  • Send communications
  • Trigger workflows
  • Change configurations
  • Interact with OT
  • Initiate automated responses

What we design for

  • Least privilege
  • Identity & authorization
  • Tool permissions
  • Tenant isolation
  • Secrets protection
  • Prompt-injection defenses
  • Knowledge poisoning
  • Excessive agency
  • Compromised tools
  • Privilege escalation
  • Human approval gates
  • Blast-radius reduction
  • Policy enforcement
  • Tamper-evident activity records
  • Cybersecurity monitoring

Auditability & evidence

Autonomous Doesn't Mean Unaccountable.

Every agent action should leave evidence. Our architectures record execution, decision context, tool activity, telemetry history and change history — designed to support governance, evidence collection and compliance programs such as SOC 2, NIST and ISO.

Questions you should be able to answer

  • What happened?
  • What did the agent observe?
  • What information did it use?
  • What decision did it make?
  • Why did it make that decision?
  • Which tool did it call?
  • Who authorized the action?
  • What changed?
  • Can the sequence be reconstructed?

Architecture can support compliance efforts; it does not by itself make an organization compliant with any framework.

evidence · run_7f3asha256 chained · append-only
observed
4 signals · link_down x3, temp_high x1
context
osm://site-north/gw-07 · state=degraded
knowledge
sop-118 rev 4 · incident-2291 (similar)
decision
restart gw-07 uplink during window
rationale
matches sop-118 §3; blast radius 1 site
approval
required · granted by on-call (field-ops)
tool_call
netctl.restart_uplink(gw-07) → 200
change
uplink restored 14:06:40Z · ticket OPS-5521
Illustrative agent execution record. Every step can be reconstructed.
The Octopus FrameworkA central core of shared context, governance and knowledge with eight connected capabilities: Agents, Data, Telemetry, Cybersecurity, KnowledgeOps, OSM, Workflows & Automation, Human Expertise.AgentsDataTelemetryCybersecurityKnowledgeOpsOSMWorkflows & AutomationHuman ExpertiseSHARED COREContextGovernanceKnowledge

Thought leadership

The Octopus Framework

Intelligent enterprises need interconnected capabilities, not isolated AI applications. Like an octopus, specialized arms act independently while staying connected through shared context, governance, knowledge and operational intelligence.

Developed by Thomas Caldwell and the Octopus book series, the framework is the intellectual architecture behind how EcoSec WorX scopes, designs and delivers every engagement.

Explore the Octopus Framework

Cloud agnostic

Your Cloud. Not Ours.

We design Agentic AI architectures for AWS, Microsoft Azure and Google Cloud — and hybrid environments when that is the right call. The platform follows your constraints, not a partnership quota.

  • AWS
  • Microsoft Azure
  • Google Cloud

Architecture is designed around

  • Your existing environment
  • Security requirements
  • Existing contracts
  • Data architecture
  • Workload requirements
  • Operational systems
  • Hybrid where appropriate

Intellectual property

Your Solution. Your IP.

We don't hold your AI strategy hostage. Your custom business logic and work product can belong to you.

Custom work product

Can belong to you

The custom business logic and work product we build specifically for your engagement can be owned by your organization.

Pre-existing EcoSec WorX components

Licensed for your solution

Where we use our reusable frameworks, libraries or building blocks to accelerate delivery, those components can be licensed to you for use within your solution.

Detailed ownership and licensing terms are defined in the applicable consulting agreement or statement of work.

We don't hand over code and disappear.

After delivery we stay available for support, maintenance, enhancements and advisory — including fractional CTO services.

  • Support
  • Maintenance
  • Enhancements
  • Architecture advisory
  • Fractional CTO services
  • AI lifecycle management
  • Knowledge-base maintenance
  • Agent optimization
  • Security reviews

Optional · Managed Agentic AI Monitoring

  • Agent failures
  • Workflow failures
  • Abnormal actions
  • Latency
  • Model usage
  • Security events
  • Tool failures
  • Integrations
  • Telemetry anomalies
  • Operational health

People

Senior Leadership. Specialist Talent When Needed.

You work directly with experienced principals. When an engagement calls for it, we assemble specialists from a deliberate expert network — rather than staffing your project from a bench.

Thomas Caldwell

Principal · Agentic AI Architect

Technology executive, entrepreneur and cybersecurity innovator with experience at Microsoft, Cisco Systems and technology startups. Thomas works across distributed systems, networking, AI and autonomous operational systems, and is the author of the Octopus book series.

  • Agentic AI architecture
  • Cybersecurity
  • Distributed systems
  • Enterprise architecture
  • Octopus Framework

Greg Ricchiuti

Principal

A core EcoSec WorX leader focused on the strategic, business and operational side of engagements — ensuring Agentic AI initiatives are tied to real business outcomes and operational realities.

  • Strategy
  • Business leadership
  • Operations

Extended expert network

  • Data scientists
  • AI engineers
  • Cloud architects
  • Cybersecurity professionals
  • Software developers
  • Frontend engineers
  • Backend engineers
  • DevOps engineers
  • Data engineers
  • Domain specialists

Next step

Have an Agentic AI Idea?

Let's determine whether it is worth building. Every engagement starts with an Architecture Sprint that ends in an explicit Go / No-Go recommendation — and sometimes the right answer is "don't build it yet."