Oxiom Systems Traceable AI delivery

AI workflow design and delivery

Build with agents. Keep the proof.

Oxiom Systems helps teams use coding agents and AI workflows without losing the decisions, review steps, or operational control needed for real delivery.

TraceWeaver turns AI-assisted work into clear tasks, review checkpoints, test evidence, and delivery records teams can trust.

Explore TraceWeaver Watch the videos Plan a workshop
Start here TraceWeaver AI development
Open the overview on YouTube

TraceWeaver control loop

Keep the brief, agent work, and proof connected.

Intent Proof Control
  1. 01 Approved brief Separate confirmed goals from open questions.
  2. 02 AI work Run coding agents inside clear task boundaries.
  3. 03 Evidence Review results and keep test evidence close.

The practice

AI workflow and solution architecture for teams.

Oxiom Systems helps teams design and deliver AI-assisted software with clear architecture, practical agent workflows, and evidence that decisions can be trusted.

I

Traceability

Goals, decisions, code changes, tests, and release notes stay connected instead of disappearing into chat history.

II

Architecture

Production AI systems still need integration, reliability, observability, security boundaries, and operational judgement.

III

Workflow systems

Practical workflow systems connect agents, tools, APIs, data, approval gates, and human review into working business systems.

AI delivery consultant

Work with a specialist AI delivery consultant.

Oxiom Systems can include a specialist virtual consultant that runs in your environment. Built on the Google Antigravity SDK, it helps check requirements, review trace records, and flag changes that need human approval.

Autonomous Oversight

The consultant works alongside developers and other coding agents. It checks whether code changes still match the approved brief, test coverage, and review steps before pull requests move forward.

  • Trace checks: Runs tw-audit to find code, tests, or requirements that no longer line up.
  • Delivery gates: Uses tw-authority-gate to flag work that has not been tied back to the approved goal.
  • Actionable feedback: Reports gaps directly into the codebase and asks developers for clarification.
Oxiom Consultant Session
$ tw-audit "check codebase traceability"
[INFO] Scanning workspace directory for TraceWeaver gates...
[INFO] Comparing active hashes with .traceweaver/intent-contract.yml...
[WARN] Finding TWCORE-041: 18 lines need review in src/billing.js
[WARN] Finding TWCORE-042: No test record links to REQ-TW-021
[PENDING] Production readiness needs a verification trail
[DONE] Trace audit complete. 2 warnings, 1 pending claim.

How the work moves

From idea to reviewed delivery, with the gaps made visible.

Idea
Scope
Plan
AI work
Review
Test
Approve
Operate

Flagship product

TraceWeaver is the control layer for coding-agent work.

TraceWeaver is open source today. It gives teams a file-based workflow for capturing the goal, approving the work, checking traceability, recording tests, and handing off releases with clear review notes.

Instruction 
Build the requested feature with tests.
Use your judgement where the brief is unclear.
Ship the smallest working version.
Proof sample 
const result = await agent.implement(featureBrief);

// Fast path: inspect the diff and run tests,
// then infer whether the feature is acceptable.
Delivery state Unbound work
Brief Agent Assumptions hidden

First-time guide

Get started in minutes.

github.com/Oxiom-Systems/traceweaver

Choose your developer environment to configure TraceWeaver. We generate the install commands and show the project files it adds.

Terminal Setup 
# Install the marketplace and plugin
codex plugin marketplace add Oxiom-Systems/traceweaver
codex plugin install traceweaver-core@traceweaver

# Start TraceWeaver for your project
tw-auto "bootstrap TraceWeaver for this project"
Project files 
my-project/
├── requirements.md               [NEW]  <- Requirements baseline
├── traceability-matrix.md        [NEW]  <- Links code and verification paths
└── .traceweaver/
    └── intent-contract.yml       [NEW]  <- Baseline hash and active checks
Read the Codex guide Plan adoption help

Video guides

Learn the TraceWeaver workflow from overview to manual control.

Start with the short overview, then follow the setup guide and the manual workflow walkthrough when you want to see every gate in the process.

Overview

TraceWeaver: Build with Agents. Keep the Proof.

A short introduction to why TraceWeaver exists and how it keeps goals, requirements, proof, and delivery notes connected.

Open on YouTube

Setup and automation

Install, Bootstrap, and Run the First Cycle.

A practical setup walkthrough covering installation, bootstrap, the project baseline, the normal loop, audit, and experimental /tw-auto.

Open on YouTube

Manual flow

Strategy, Requirements, Work, Review, and Debug.

The hand-driven process: strategy, ideation, requirements, planning, work, traceability, review loops, and where debugging fits.

Open on YouTube

Online course

Buy the TraceWeaver course pack.

Get access to the three online course videos, expanded course notes, and practical handouts for learning the TraceWeaver workflow without joining a live workshop.

Included

Three videos plus learner PDFs.

  • Core ideas for agent-assisted coding
  • Key source-grounded workflow concepts
  • Applied TraceWeaver deep dive
  • Course notes and watch-along handouts
$100 TraceWeaver online course

Check out securely with PayPal. After payment, follow the return link to open the course videos, notes, and handouts.

Includes three course videos, expanded course notes, and watch-along handouts. For access help, email hannes.zietsman@oxiomsystems.com with your PayPal receipt.

Why it matters

The difference shows up when behavior must be defended.

Question
Prompt-only agent work
TraceWeaver-controlled work
Why does this feature exist?
Usually inferred from the prompt or chat context.
Mapped to the approved goal, requirement, or exception.
What happens to assumptions?
They often become implementation choices.
They become visible gaps, questions, or change notes.
How is done proven?
The feature runs and appears complete.
Behavior is backed by test results and review evidence.

Workshops

Get notified when TraceWeaver workshops open.

Oxiom workshops teach practical agent collaboration: how to turn rough ideas into scoped tasks, send unclear decisions back to people, review AI output, and keep enough proof for real delivery decisions.

Join the notification list for upcoming live sessions, course cohorts, and related TraceWeaver workshop material.

AI workflow systems

Custom AI systems need more than a model call.

Oxiom designs and implements practical AI workflow systems: agents, retrieval, tools, approvals, APIs, monitoring, and fallback paths.

A

Workflow

Convert business processes into agent-assisted flows with clear human checkpoints and recoverable state.

B

Integration

Connect AI components to business systems, APIs, databases, documents, and operating tools.

C

Operations

Design for monitoring, proof records, rollout control, failure modes, security boundaries, and maintainability.

Work with Oxiom Systems

Bring the AI workflow you need to make real.

Share the system you are building, where agents should help, and what level of architecture, workflow design, or team enablement you need.

  • TraceWeaver adoption and workflow design
  • Private workshops for teams adopting coding agents
  • AI workflow systems and prototypes
  • Solution architecture for real-world AI implementation