SR&ED for AI & ML teams.
AI work is a strong SR&ED fit when you're advancing beyond known methods. But the CRA scrutinizes AI claims closely, so evidence-linked documentation matters more here than in any other field. That's exactly what Chrono is built to produce.
What qualifies in AI & Machine Learning?
Eligibility comes down to one test: did your team work through genuine technical uncertainty? In ai & machine learning, that usually looks like this.
- Developing novel model architectures
- Training experimentation where the outcome was uncertain
- Building data pipelines to solve real technical constraints
- Improving model performance past documented limits
- Adapting research to a new domain with unknown results
What a claim looks like
A team developed a model architecture after standard approaches failed to converge.
A company built a training pipeline to handle data at a scale existing tools couldn't.
An AI firm adapted a research technique to a domain where it had never been proven.
How Chrono builds your claim
Chrono reconstructs defensible, evidence-linked timesheets and technical narratives from the records you already keep. No manual time tracking required.
- Experiment tracking (MLflow, Weights & Biases)
- Git history
- Compute and training logs
- Evaluation results
AI & Machine Learning, answered
Is fine-tuning or calling an API eligible?
Using existing models as-is generally isn't. Novel work to overcome a technical limitation, where the result was genuinely uncertain, can be.
Why is AI scrutinized more?
The CRA looks hard at whether the work advanced the field or simply applied known methods. Evidence-linked documentation, tying each claim to real experiments, is what defends an AI claim under review.
See what your AI & Machine Learning claim is worth.
Estimate your credit in two minutes, then let Chrono build the claim from the data you already have.