01Problem Space
The Context Gap
Standard models are powerful but amnesiac. Without grounded state, they drift. In the enterprise, context is history, relationships, and intent.
Intelligence that scales sovereignty.
Founded in Melbourne to close the enterprise AI gap — a real OS for autonomous agents, with governance and audit trails built in.
AEOS_DashboardAnalyticsSettings
AgentOrchestrator.tsx
TypeScript1import { Agent } from '@alias/core';
2import { workflow } from '@alias/orchestrator';
3
4export const pipeline=()=>{
5// Orchestrate agent swarm
6return(
7<workflow.run agents={swarm}>
8<Agent role="analyst"/>
9</workflow.run>
10)
11};
*Compiled successfully in 420ms
StatusProduction
Deployment URLalias.dev/v2
Branchmain
Latest Commit8f2a9c (Just now)
Live Traffic1.2k / min
Convex_Primary
Connection Pool: 45/100
OK
Agent Cache1.2GB
CPU Usage32%
Memory48%
More than just AI.
Systems that deliver.We combine ontology-first design, governed agent orchestration, and production-grade infrastructure to build AI systems that don't just demo well -- they ship.
Workflow Specv2.0.24
01_ONTOLOGY
Ontology-First Design
Every engagement starts with a robust knowledge graph. We map your domain, constraints, and decision points before writing a single line of code.
Knowledge Coverage100%
02_GOVERNANCE
Governed Agent Orchestration
Multi-agent workflows with approval gates, audit trails, cost controls, and human-in-the-loop checkpoints built in from day one.
Agent Accuracy94.2%
03_INFRA
Production-Grade Infrastructure
Battle-tested stacks using Next.js, Convex, Vercel, and Claude/GPT -- with observability, guardrails, and zero-downtime deployments.
Next.jsConvexClaudeVercel
StackFULL STACK
/ Capabilities
What We Build
01
Agent Strategy
Executive framing, operating model and system design for AI-native organisations.
DiscoveryOntologyRoadmap
02
Workflow Automation
Automate decision and delivery loops with governed agent swarms and human-in-the-loop checkpoints.
AgentsOrchestrationApprovals
03
Agentic Infrastructure
Production-ready stacks with guardrails, observability, cost controls, and zero-downtime deployments.
ConvexVercelMonitoring
04
Interface Design
Operator dashboards, copilots and execution surfaces that make AI systems usable by real teams.
DashboardsCopilotsUX
05
Decision Intelligence
Signals, observability and decision feedback loops that turn agent outputs into measurable business outcomes.
AnalyticsFeedbackROI
/ Methodology
Execution Pipeline
STEP 01
Discover
Map your ontology, workflows, and constraints.
STEP 02
Design
Architect the agent system, governance, and integrations.
STEP 03
Develop
Build, test, and iterate with 2-week sprints.
STEP 04
Deploy
Ship to production with monitoring and guardrails.
STEP 05
Optimise
Measure outcomes, tune agents, scale capabilities.
Why Choose
ALIAS?
ALIAS?
Ontology First
Every engagement starts with a robust knowledge graph that maps your domain, constraints, and decision points.
Outcome-Driven
Measured by delivered business outcomes, not hours billed. We succeed when your metrics move.
Sovereign AI
100% Australian owned. Data residency guaranteed. Your IP stays yours, always.
10x Faster
2-week sprints vs 6-month enterprise projects. Ship in weeks, not quarters.
No Lock-in
Open standards, API-first, you own all code. Walk away any time with everything you paid for.
We Run ALIAS
We use our own platform to run our business daily. If it's not good enough for us, it's not ready for you.
/ Architecture Showcase
Intelligence is not magic.
It is engineering.
Most AI stacks are assembled, not architected. ALIAS treats context, ontology, orchestration, and governance as one operating layer — so every agent you deploy is governed, aligned, and operable from day one.
Architecture Assembly
One context layer. Many operators. Zero blind execution.
When context is a shared layer, every agent operates from the same ontology. Decisions align to governance boundaries. Orchestration happens against a single source of truth, not scattered assumptions.
Context
Grounded
Authority
Explicit
Execution
Observable
Unified Context
Live entity memory across people, agents, and systems.
Graph Coordination
Relationships, permissions, and workflow state remain explicit.
Governed Execution
Every operator path is observable, reviewable, and bounded.
02Foundation Layer
Unified Context Engine
UCE fuses entities, processes, and fragmented knowledge into a single operational truth so agents reason from live system state instead of stale snapshots.
03Protocol
Ontology First
We do not deploy agents before the domain is structured. Deterministic behavior in probabilistic systems starts with explicit ontology, policy, and naming.
04Semantic Layer
Dynamic Knowledge Graph
Beyond vector recall. The graph maps entities, attributes, and changing relationships in real time, so the system learns the business physics it operates inside.
05Execution Layer
Agentic Work Environment
Humans and agents operate together. Authority is explicit. Escalation is designed. Agents are operators inside infrastructure, not detached chat surfaces.
06Governance
Control by Design
RBAC, auditability, sovereign deployment, and observable workflows are built in from the start, not layered on after risk is already in production.
Operational Intelligence
Move from disconnected experiments to governed systems that run.
Unified Context Engine
UCE
The Organisational Knowledge Graph
Meta-Orchestration System
MOSAIC
The Cognitive Collaboration Framework
Agentic Work Environment
AWE
The Secure, Scalable Runtime
/ Social Proof
Client Logs
1 / 5
/ Investment
Engagement Models
*Choose the engagement model that fits your stage.
Strategy Sprint
Fixed Scope
A focused engagement to map your AI opportunity and build an implementation brief.
- Domain discovery workshop
- Workflow mapping & analysis
- Agent system framing
- Implementation brief
- Priority roadmap
Recommended
Build Partner
Monthly
Ongoing hands-on technical leadership with agentic workflow design and deployment.
- Agentic workflow design
- Copilots & automations
- Observability & guardrails
- Hands-on tech leadership
- 2-week sprint cadence
Embedded ALIAS
Custom
Full integration into your organisation for cross-team orchestration at scale.
- Cross-team orchestration
- Governance infrastructure
- Long-range operating model
- Memory & knowledge systems
- Executive alignment
/ Documentation
Common Queries
What makes ALIAS different from other AI consultancies?
We start with ontology, not demos. Every engagement begins by mapping your domain, constraints, and decision points. We build governed agent systems -- not chatbots. And we run ALIAS on our own platform, so we ship what we actually use.
How long does a typical engagement take?
Strategy Sprints run 2 weeks. Build Partner engagements are monthly with 2-week sprint cadence. Most teams see their first agent workflow in production within 4 weeks.
Do you work with specific AI models?
We are model-agnostic. We work with Claude, GPT, Gemini, Grok, and open-source models. We choose the right model for each task based on cost, latency, accuracy, and your data residency requirements.
What industries do you serve?
Enterprise, fintech, healthcare, logistics, proptech, and government. Any organisation with complex workflows and decision points is a good fit.
Can you work with our existing systems?
Absolutely. We are integration-first, not rip-and-replace. We connect to your existing tools, databases, and APIs. No vendor lock-in, open standards, you own all code.
/ Tech_Stack
Next.js
Convex
Vercel
Three.js
GSAP
Tailwind
TypeScript
Claude
GPT
Resend