Normalized claim
Time: 30% increase
Smokeball reported up to 30% more billable hours captured.
Smokeball automates legal admin workflows using Amazon Bedrock and Amazon SageMaker
Use case typeLegal workflow automationUpdated Jun 13, 2026
Smokeball is a Sydney-based legal practice management company serving more than 6,000 law firms across Australia, the UK, and the US. The company built Smokeball AI to reduce administrative work that takes time away from billable legal work. The implementation targets document creation and review, client intake, and time tracking workflows that are common in law firms and directly affect productivity and revenue capture.
Reported outcomes
+30%
timeTime & speed
3 hourstime5 minutestime
Strategic outcomes
Scale & capacityReduced administrative work for law firmsNew product / capabilityLaunched AI legal workflow suiteCustomer experience & trustImproved client onboarding formsCost efficiencyReduced legal costs for clients
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Time: 3 hours decrease
The company said lawyers can save up to 3 hours per day on administrative tasks.
Normalized claim
Time: 5 minutes decrease
Form creation and population time dropped from about one hour to 5 minutes.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Smokeball
- Provider
- AWS
- Maturity
- Unknown
- Linked source
- AWS Customer Story
No explicit deployment-stage evidence found.
Customer identity supportedSource describes one deploymentMaturity evidence evaluated
Primary read
Use case focus
Showing 3 of 4
- 1Document automation
- 2Legal workflow automation
- 3Client intake automation
- Law firms spent too much time on manual administrative work such as document creation and review, client intake, and time tracking.
- These repetitive tasks reduced billable hours, increased operating costs, and limited lawyers’ ability to focus on client work.
- Smokeball built a suite of AI tools called Smokeball AI on AWS.
- Archie uses Amazon Bedrock and Claude V3 to provide matter-based document summarization, question answering, and correspondence drafting.
- Intake uses Amazon SageMaker to process existing forms and generate customized versions for client onboarding.
- AutoTime combines Amazon Bedrock and Amazon SageMaker to automate time tracking and billing.
- The platform also uses AWS Lambda, Amazon SQS, and Amazon EKS to support scalable, secure AI workflows and integration with existing legal management systems.
- Smokeball reported up to 30% more billable hours captured.
- The company said lawyers can save up to 3 hours per day on administrative tasks.
- Form creation and population time dropped from about one hour to 5 minutes.
- The tools reached public beta within six months, and the company said the automation reduced legal costs for clients.
Architecture
Smokeball AI is implemented on AWS using Amazon Bedrock for generative AI assistance with Claude V3, Amazon SageMaker for machine learning workflows, AWS Lambda for serverless response handling, Amazon SQS for queue-based orchestration, and Amazon EKS for scalable containerized infrastructure. The tools are integrated into legal practice workflows for document processing, intake, and automated time tracking.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: May 13, 2026Publisher: AWS Customer StoryEvidence: PrimaryConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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