Sources
Every official record the agent reads, normalised into one place. Audit reports, tender records, budget papers, FOI statistics.
Case Study · 21 Day SprintPublished 09 Jun 2026
We built a government accountability engine in 21 days.
A defined problem, taken from idea to a live agentic product in one sprint. This is how Altitude Group ships new agentic products — fixed scope, fixed timeline, fixed price.
21 days
from idea to live product
21+
official sources connected
Daily
ingestion and detection
From $30k
fixed price, fixed scope
Most organisations sit on a problem they know is solvable with AI. They have the data. They have the use case. What they do not have is a path from idea to a live product that runs every day.
So the idea sits in a deck. It waits for a hire, a budget cycle, or a research project with no end date.
Blackline Intelligence is the counter-example. A defined problem, taken from idea to a working agentic product in 21 days.
The Problem
The records are public. Nobody connects them.
Australian governments publish a flood of records. Audit reports. Tender records. Budget papers. FOI statistics. The information is public.
The records sit across more than 21 disconnected sources. No single person reads all of them. No single system connects them.
So the patterns stay buried. A funding line in one document, an audit finding in another, a refused FOI request in a third. The dots exist. Nobody is paid to match them at scale, so nobody does.
This is the pattern in almost every business. The advantage sits unused in data, scattered across systems, with no agent reading it in real time.
The System
Blackline Intelligence.
Blackline Intelligence reads the government's own records every day and surfaces where money and transparency break down. It pulls from official sources — ANAO performance audits, AusTender contract records, portfolio budget statements, OAIC FOI statistics — cross-references them, finds the anomalies, and produces a structured output with the source attached to every claim.
No analyst. No week of spreadsheet work. A system that runs on its own and shows its working.
Sample finding · OAIC FY2024-25
What it surfaced from one source.
86.3%
FOI requests not granted in full
33,995
Of 39,390 across 304 agencies
41
Agencies granting zero in full
2.3%
Defence FOI granted in full
- — The Department of Defence took $46.8 billion in funding, then granted 2.3% of FOI requests in full. 23 of 1,006.
- — The FOI regulator granted 5.8% of requests against itself. 32 of 548.
Every figure traces to a primary source. The point is not the outrage. The point is a machine found it, attributed it, and could do it again tomorrow with new data.
What agentic development actually means
Not a chatbot bolted onto a workflow.
A system of focused agents, each with one job, all reading and writing the same shared memory, executing without a human driving every step. For a new product, that translates into a clear shape:
Signals
The patterns worth surfacing, defined before any code. Funding lines that do not match outcomes. Audit findings that recur. FOI refusals that cluster.
Decisions
What the agent flags. What it leaves alone. The boundary between noise and a finding worth a human's time.
Outputs
A structured result with a source trail on every claim. No untraceable numbers. Every figure carries its primary source.
The hard part was never the AI model. The hard part is the operating discipline — defining the signals, drawing the boundaries, validating the outputs, and shipping it as a real product instead of a demo.
How it was built · The 21 Day Sprint
One sprint. A live product at the end.
This did not take a quarter. It took one defined sprint — the same delivery model behind every Altitude Group product.
- Week 1
Scope and spec
Decompose the workflow into sources, signals, decisions, and outputs. Decide what it will surface and what it will not. Agree the success measure before any code. By the end of the week the build has no open questions.
- Week 2
Build
Agentic development against the spec. Wire each source into a normalised store. Build the signal detection. Produce structured outputs with a source trail on every claim. No untraceable numbers.
- Week 3
Harden and ship
Testing and QA gates. Launch live. Documentation and handover. One sprint. A working agentic product at the end, running on real data. Not a prototype. Production.
Why a sprint beats an open-ended build
Constraints are the feature.
A research project drifts. Scope expands, the timeline slips, and the budget grows with no fixed end. Most AI ideas die there.
A sprint forces the opposite. Fixed scope. Fixed timeline. Fixed price. The constraints turn a vague ambition into a shippable product because every decision has a deadline attached.
You do not get a slide deck and a maybe. You get a live product in 21 days, fully project managed.
Fixed scope
Fixed timeline
Fixed price
What this proves for your project
The gap is rarely the technology.
Blackline is one example of a general pattern. A defined problem buried in data, turned into a live agent in three weeks.
If you have a workflow that should already run on AI, the gap is rarely the technology. The models exist. The use case is clear. What is missing is the discipline to turn it into something live that runs every day.
That gap is what the sprint closes.
About Altitude Group
Have a problem buried in data?
Altitude Group takes defined business problems and turns them into working agentic products in 21 days. Fully project managed. Fixed scope. Fixed price. Book a discovery call and we will pressure test whether your problem fits a sprint.
From $30,000. Fixed price. 21 days.
See what the engine surfaces at blacklineintelligence.xyz
FOI figures sourced from OAIC Annual FOI Statistics FY2024-25, foi.gov.au. Funding figures from the 2025-26 Portfolio Budget Statements, budget.gov.au. Each figure should be confirmed against its primary source before republishing.