R&D Intelligence Dashboard

FY26 monitoring · Last scanned just now

Claim preparation active

Estimated opportunity

Estimated tax benefit

Confirmed by your specialist

R&D projects detected

Potential R&D activity

Evidence items found

Across connected tools

Claim readiness

Moderate readiness

Detected R&D projects

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Likely R&D2 gaps

Sensor Calibration Algorithm

82%

FlowForge developed a new calibration algorithm to improve sensor accuracy in unstable industrial environments where temperature, vibration, and signal interference caused inconsistent readings.

75 evidence items$178K est. eligible spendHigh

Possible R&D2 gaps

Automated Defect Detection Model

57%

FlowForge is building a computer vision model to detect inconsistent surface defects under variable lighting and material conditions, removing the need for manual visual inspection on the production line.

57 evidence items$146K est. eligible spendMedium

Needs review2 gaps

Manufacturing Process Optimisation

34%

FlowForge trialled changes to the production process to reduce material waste during a new production run. The trial involved adjusting machine parameters and material handling sequences.

16 evidence items$68K est. eligible spendLow-medium

Evidence completeness

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Technical tickets91%

Commits / version history87%

Test reports64%

Cost records38%

Experiment logs29%

Cost records and experiment logs require attention before lodgement.

Qualifying activity timeline

Jul 2025
Initial prototype design commenced
Jira
Aug 2025
Calibration drift issue identified in field tests
Jira
Sep 2025
First calibration trial failed under vibration
Drive
Oct 2025
Adaptive filtering algorithm iteration
GitHub
Nov 2025
Second field test completed — partial improvement
Drive
Jan 2026
Defect detection model development initiated
Jira
Jan 2026
Latency issue detected in calibration pipeline
Slack
Feb 2026
First model evaluation — precision insufficient
Drive
Mar 2026
Manufacturing process optimisation trial commenced
Jira
Apr 2026
Custom CNN with lighting normalisation in progress
GitHub

Recently detected R&D signals

View evidence

“Calibration drift unresolved after v2 test”
Sensor Calibration Algorithm · 2 hours ago
“New filtering approach added to sensor pipeline”
Sensor Calibration Algorithm · Yesterday
“Team discussed uncertainty around field accuracy”
Sensor Calibration Algorithm · 3 days ago
“Prototype test report uploaded to shared folder”
Automated Defect Detection Model · 4 days ago
“Engineering contractor invoice linked to Project 1”
Sensor Calibration Algorithm · 1 week ago

Overall claim readiness

Moderate readiness

Strong technical signals detected, but cost evidence and documentation gaps remain.

Eligible expenditure estimate

$392,000

R&D-linked expenditure detected · Medium-high confidence

Engineering salaries

$245K

medium

Contractor costs

$67K

medium

Prototype materials

$46K

medium

Cloud / compute

$23K

low

Testing costs

$11K

high

Team contribution

Maya ChenML Engineer
38
Liam BrooksProduct Engineer
31
Anika PatelManufacturing Lead
24
Daniel RossCTO
18

R&D signals detected per team member

Risk flags

View all gaps

Cost evidence incomplete — salary allocation unconfirmed
Some activity in Project 3 may be BAU engineering
Project 3 lacks a documented experimentation history
Contractor costs require scope confirmation

Recommended next actions

Submit Project 1 to Canopy for preparation
Upload Project 2 model comparison test results
Confirm team involvement percentages by project
Add technical uncertainty statement for Project 3
Talk to your Canopy specialist

4 risk flags and 11 documentation gaps require attention

Addressing these before lodgement may strengthen the claim position.

View gaps

Figures update automatically as new evidence is connected. Your Canopy specialist will confirm all positions during claim preparation.