We build the platform. Then we run it.
Data Forge designs, ships and operates production software for Australian businesses: the services, the data, the AI agents, the infrastructure underneath and the measurement on top. We run our own group of companies on it first.
Estate snapshot, measured from the repository on 2026-09-09
Running services, by plane
snapshot 2026-09-09
| Status | Service | Role | Runtime |
|---|---|---|---|
| Platform & infrastructure | |||
| Deployed | auth-engine | Rust | |
| Deployed | auth-idp | Rust | |
| Deployed | authz-projector | Go | |
| Deployed | config-vault | Rust | |
| Deployed | telemetry-gateway | Go | |
| Data platform | |||
| Deployed | intel-event-pipeline | Go | |
| Deployed | intel-clickhouse-consumer | Go | |
| Deployed | intel-orchestrator | Python | |
| Deployed | graph-sync | Go | |
| Deployed | analytics-etl | Go | |
| Applied AI & agents | |||
| Deployed | agent-runtime | Go | |
| Deployed | knowledge-graph | Go | |
| Deployed | forge-context | Go | |
| Deployed | code-intel-mcp | Go | |
| Deployed | rag-memory-mcp | Go | |
| Deployed | embedding-gateway | Go | |
| Product engineering | |||
| Deployed | core-api | Go | |
| Deployed | surebi-api | Go | |
| Deployed | surebi-reports | Go | |
| Deployed | solar-api | Go | |
| Deployed | quote-calculator | Rust | |
| Deployed | finance-api | Go | |
| Growth & measurement | |||
| Deployed | intel-collector-api | Go | |
| Deployed | intel-lead-scoring | Go | |
| Deployed | intel-capi-dispatcher | Go | |
| Deployed | intel-compliance | Go | |
| Deployed | growth-studio-api | Go | |
| Automation for operators | |||
| Deployed | notification-handler | Go | |
| Deployed | workflow-engine | Rust | |
| Deployed | scheduling-optimizer | Rust | |
| Deployed | lead-assignment-worker | Rust | |
| Deployed | realtime-gateway | Go | |
Showing 32 of 79 services and workers in the estate.
See the whole boardSix planes. One estate. All of it operated by the people who built it.
Most consultancies have a services list. This is a running system. Each band below is a plane of that system, what it promises, and the real services that carry it today. Measured from the repository on 2026-09-09.
Running services, wired to their stores
snapshot 2026-09-09
54 connections declared in the deploy manifests.
32 nodes · 6 stores
Platform & infrastructure
The layer nothing above it should have to think about.
Kubernetes on immutable, API-managed nodes. GitOps reconciliation, one image lane with provenance gates, and a release train so a deploy is a decision rather than an accident. Identity, secrets, certificates, storage and backups are part of the build, not a follow-up ticket.
Full detail- Talos Linux Kubernetes, nine nodes in Perth
- Argo CD GitOps with pinned manifests and a release train
- One image lane with provenance and entrypoint gates
- OIDC identity: auth-engine sessions, auth-idp provider, SpiceDB
- config-vault secrets with provenance and audit
In the estate
- auth-engine
- auth-idp
- authz-projector
- code-intel-toolchain
- config-vault
- config-vault-cli
- config-vault-reconciler
- +1 more
Data platform
One store, one job. Nothing quietly doing three.
Most data problems are placement problems: events in the transactional database, relationships in a JSON column, embeddings in whatever was nearest. We put each kind of data in the store built for it and keep every derived layer rebuildable from its source.
Full detail- Postgres as the transactional system of record
- ClickHouse for append-only events and analytics, queried in SQL
- Redpanda as the transport between services, with declared topics and dead-letter queues
- FalkorDB graphs for identity and code relationships, queried in Cypher
- Qdrant vector search for embeddings, tenancy enforced as a payload filter
In the estate
- analytics-etl
- analytics-service
- data-pipeline
- dataforge-pg-migrations
- graph-sync
- intel-clickhouse-consumer
- intel-event-pipeline
- +3 more
Applied AI & agents
Agents wired into real systems, not a chat box on the side.
We build agent runtimes and tool servers that read and write the actual estate: the work ledger, the code graph, the event bus, the warehouse. Retrieval runs over your own corpus with tenancy and consent already enforced, so an agent can be useful without being dangerous. Nothing gets write access before it has been evaluated.
Full detail- Agent runtime and orchestrator services
- MCP tool servers over Postgres, ClickHouse, Redpanda, Qdrant, Prometheus and OpenProject
- A code-intelligence graph for impact analysis before a change ships
- Knowledge graphs for entities and relationships
- An embedding gateway that routes to Gemini or a local Ollama model
In the estate
- agent-api
- agent-kb-embedder
- agent-kb-mcp
- agent-orchestrator
- agent-runtime
- clickhouse-mcp
- code-intel-mcp
- +16 more
Product engineering
The right language for the job, in one coherent codebase.
Go for domain services, Rust where the work is CPU-bound, Python where the work is data and machine learning, typed React on the front and Astro for the sites. One monorepo, one build graph, and shared packages for the things every surface needs, so a capability is built once and used everywhere.
Full detail- Go domain APIs on a standard service contract
- Rust workers for quoting, scheduling, search and media
- Python services for documents, reports and property intelligence
- Vite and React operator consoles and customer apps
- Astro marketing sites built for Core Web Vitals
In the estate
- cashflow-api
- core-api
- deal-checklist
- document-processor
- finance-api
- image-processor
- integrations-api
- +12 more
Growth & measurement
Numbers you can defend when the spend is questioned.
Client-side analytics quietly lies. Consent gating, ad blockers and platform attribution all bend the shape of the truth. We collect server-side, score the bots out, deduplicate conversions into Meta and Google, export raw events to the warehouse, and run ad accounts against real jobs rather than platform-reported conversions.
Full detail- Server-side event collection with browser fingerprint capture
- Bot scoring before an event counts
- An identity graph and recency-weighted lead scoring per brand
- Meta and Google Conversion APIs with event deduplication
- GA4 with raw export to BigQuery
In the estate
- cms-analytics-sync
- growth-os-api
- growth-studio-api
- intel-activation
- intel-analysers
- intel-analysers
- intel-capi-dispatcher
- +5 more
Automation for operators
The repetitive work handled, permanently.
Lead routing, notifications with a delivery record per lead, franchise and territory workflows, scheduling, accounting and CRM integrations, and internal consoles so an owner can see the whole business without asking anyone. This is the original promise of Data Forge: technology that gives people their time back.
Full detail- A durable notification lane with a delivery record per lead
- Round-robin lead assignment and territory routing
- A workflow engine for work-item transitions and triggers
- Schedule optimisation for field availability and conflicts
- Xero and Pipedrive integrations
In the estate
- command-centre-api
- csv-import-worker
- lead-assignment-worker
- notification-handler
- realtime-gateway
- scheduling-optimizer
- workflow-engine
The estate, counted.
Every claim on this site maps to something in the repository or the cluster. These are the numbers a script reads out of the codebase, not a marketing estimate.
Repository
- Services and workers
- 79 (55 Go, 16 Rust, 8 Python)
- Apps and sites
- 14
- Shared packages
- 9
- Kubernetes manifests
- 496
- SQL migrations
- 609
- CI workflows
- 37
- Commits since 2025-12
- 7,390
- Merged pull requests
- 2,937
Cluster
k8-forge · 9 nodes
One Dell PowerEdge R740xd (72 cores, 256 GB, an NVIDIA P40) and eight HP EliteDesk minis running Talos Linux, in Perth, reached over Tailscale.
Stores, one job each
- Postgres
- system of record
- SQL
- ClickHouse
- events and analytics
- SQL, columnar
- Redpanda
- transport between services
- Kafka API
- FalkorDB
- relationship graphs
- Cypher
- Qdrant
- embeddings
- vector search
- MinIO
- objects and backups
- S3 API
All six stores run on node-9 by design: the one machine in the fleet built to hold state.
Nine nodes, one job each
| node-1 | HP EliteDesk 800 G5 | 6c / 16 GB | control plane | |
| node-2 | HP EliteDesk 800 G5 | 6c / 16 GB | control plane | |
| node-3 | HP EliteDesk 800 G5 | 6c / 16 GB | control plane | |
| node-4 | HP EliteDesk 800 G5 | 6c / 16 GB | worker | |
| node-5 | HP EliteDesk 800 G4 | 12c / 32 GB | worker | |
| node-6 | HP EliteDesk 800 G4 | 12c / 32 GB | worker | |
| node-7 | HP EliteDesk 800 G4 | 12c / 32 GB | worker | |
| node-8 | HP EliteDesk 800 G4 | 12c / 32 GB | worker | |
| node-9 | Dell PowerEdge R740xd | 72c / 256 GB, NVIDIA P40 | data plane23 workloads pinned |
Runs the SURE group first.
Data Forge operates a group of Australian service brands on the same platform it builds for clients. Every system on this page carries real bookings, real leads and real invoices before it is offered to anyone else.
-
SURE Building Inspections
surebuildinginspections.auBuilding and timber-pest inspections across Western Australia and New South Wales, run as franchise territories.
Systems
- A twelve-thousand-page Astro site generated from a content pipeline, with a searchable index of roughly ten thousand building defects
- Lead capture, booking and franchise routing through a Go API
- Server-side tracking, conversion APIs and the Google Ads operation behind them
- Inspection-report intake, parsing and a defect knowledge base
-
Systems
- A solar CRM with quoting, proposals and installation pipeline
- A Rust quote calculator for pricing rules and margins
- Schedule optimisation for installer availability
- Xero integration and customer notifications
-
Systems
- A customer-acquisition site with a lead lane straight into the core API
- Quoting and job management on the shared platform
-
SURE Pest Control
On the shared platform
Pest management, on the same platform primitives configured for a different service line.
Systems
- Marketing site and enquiry flows
- Shared lead routing and notifications
Also built for clients
-
Beauty
A booking and business-management platform with online payments, an admin dashboard and its own booking and customer services.
-
Financial education
A client intake wizard and an adviser cockpit that turns a household budget into consequences a couple can feel, built for live sessions on a big screen.
-
Hospitality
A specialty coffee brand site and the API behind its events and products.
How work moves.
The same flow runs our own estate and every client engagement. Four of the six stages end at a gate you hold. Nothing ships unverified, and merging is never the finish line.
-
Scope
gate · path
We write down the goal, the success criteria, the systems touched and the people needed. You see it before anything else happens.
-
Design
gate · spec
One-way doors, meaning data models, wire contracts and store choices, are designed and agreed on paper. Reversible things ship lean.
-
Plan
gate · plan
The spec becomes an ordered task list with a file-ownership map, so parallel work never collides.
-
Build
no gate
Specialists build in isolated worktrees against a shared ledger. You can see what is in flight and what is blocked without asking.
-
Verify
no gate
Tests, lint and type gates across everything affected, then adversarial review for anything high-stakes. Red does not ship.
-
Ship
gate · ship
Merging deploys nothing. An image is built, pinned, released and reconciled, and the change is done when a probe shows it running.
What done means
A change is done when the pod is running the new image and a probe shows traffic. Not merged, not staged, not "should work".
Who is behind it.
Build things that keep working when nobody is watching them.
Jacob, founder of Data Forge. An advanced degree in AI, machine learning and data science, applied to business. Taught data science at Curtin University and the Institute of Data. More than ten years running companies, including a marketing business with over fifty staff. Owner-operator of the SURE group.
I used to run a multi-million dollar marketing company with over fifty staff. On paper it looked like success. Behind the scenes I was constantly putting out fires, working around the clock, and slowly burning out.
Then everything changed. I lost my mum, and I realised how much I had missed while buried in the grind. I left the company, moved home, and began rebuilding with a new goal: create freedom, not stress.
Open a conversation.
Tell us what you run today and what keeps breaking. We will tell you, plainly, what we would do about it and whether we are the right people to do it.