Swindon Borough Council used generative AI through Amazon Bedrock to convert complex documents into Easy Read format for residents with learning disabilities.This reduced document production from hours to minutes and cut costs while improving accessibility and preventing resident exclusion.
Use case type
Document automation
Generates, processes, and routes documents automatically to remove manual paperwork.
73
60
12
27 mo
Adoption over time
Documented cases per month
By case publish month · completed months only
50 cases documented across 37 months (Jul 23 – Jul 26), peaking at 12 in May 2026.
8 earlier cases before Jul 23 not shown
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
Company examples
Use cases of this type
10 shown from 73 use cases
KPMG: KPMG Clara AI agentic audit platform on Azure
KPMG International modernized its global audit process with KPMG Clara AI, a cloud-based smart audit platform used across member firms worldwide.The platform analyzes whole datasets instead of relying on sampling, automates documentation and substantive audit procedures, and grounds agents in enterprise data for compliant, secure use across regulated jurisdictions.KPMG built the solution on Azure AI Foundry, Azure AI Search, Azure OpenAI in Foundry Models, Azure AI Content Understanding, Azure App Service, Azure Cosmos DB, and the Microsoft Agent Framework.
PlanRadar, a Vienna-based B2B software company for construction and real estate, built SiteView as a visual documentation add-on to its platform.The solution uses 360-degree camera footage uploaded to Amazon S3, extracts metadata, combines camera views, blurs people for GDPR compliance, and uses machine learning and Amazon Nova Foundation Models via Amazon Bedrock to analyze floor plans and generate interactive walkthroughs.SiteView aligns captures from different dates so users can compare progress over time in one place.
Upsure case study | Google Cloud
Upsure is an insurtech company headquartered in India that helps insurers reduce operating costs and improve sales, productivity, and revenue.To meet strict regulatory requirements, scale cost-effectively, and support its AI roadmap, Upsure moved to a full cloud environment on Google Cloud.The company is exploring Vertex AI and Gemini to help insurers automate anti-money-laundering checks, KYC scoring, lead scoring, claims automation, and document creation.
Oper Credits case study | Google Cloud
Oper Credits uses Google Cloud's Vertex AI and Kubernetes to automate mortgage processes, reduce errors, and improve borrower and bank experiences.The company built a white-label platform integrated into partner banking institutions and uses Vertex AI to analyze borrower documents and support recommendations for advisors and borrowers.
TetriXX case study - Google Cloud
Singapore-based startup TetriXX helps customers save up to millions of dollars per year by eliminating logistics inefficiencies.With Google Cloud, TetriXX provides an AI platform that turns raw data from transportation and logistics invoices into clear, actionable insights.Using Vertex AI and the Agent Development Kit, TetriXX rapidly develops new AI features and agents, moving them from R&D to production with ease.The platform also integrates data from external sources to fully inform agent outputs, ensuring they’re accurate, complete, and ready to drive smarter decision-making.Internally, the organization uses Gemini 3 Pro, Gemini Gems, and NotebookLM to support competitor analysis, consistent responses across functions, and founder knowledge capture.
Motorway case study | Google Cloud
Motorway is a UK used car marketplace that uses Google Cloud AI to improve vehicle valuation and document validation at scale.The company uses Gemini 1.5 on Vertex AI to extract text from digitized service history papers, classify document types, extract service events, and flag cases that need follow-up with sellers.Motorway also uses Vertex AI models and endpoints in its Real-Time Price Machine to generate instant valuations for used cars and improve pricing accuracy and trust between sellers and dealers.
AgeChecker.Net uses Document AI and Vertex AI to automate age verification and reduce driver’s license review time
AgeChecker.Net provides ecommerce age verification services for alcohol, CBD, and tobacco compliance.The company uses Google Cloud infrastructure and AI services to scale its verification workflow, reduce manual handling of low-quality driver’s license images, and improve response to changing regulations.
Parameta, a division of TP ICAP, automated regulatory compliance reviews using generative AI on AWS, reducing review time from 1 month to minutes.The compliance team had been manually reviewing regulations in PDFs and mapping them to products and documentation to determine compliance.Parameta built the solution with AWS prototyping support in about 3 weeks.
Carousell: using Gemini/Vertex AI + BigQuery to automate listings and run bulk fraud inferences
Carousell Group, a multi-category classifieds and recommerce marketplace, used Google Cloud generative AI and data services to improve seller listing creation, scale fraud analysis, and automate internal workflows.The company built a new "List with AI" experience that lets sellers upload a short video or photos and uses Gemini's multimodal capabilities to generate listing titles, descriptions, category, price, condition, and style variants for review.Carousell also moved fraud model bulk inference to an integrated BigQuery and Vertex AI workflow so it can analyze its full chat dataset and iterate much faster than before.Internally, Carousell created a Gemini-based translation workflow and a secure Slack bot that answers HR questions from policies stored in Google Drive.
Common questions
Document automation at a glance
- How many document automation use cases are documented?
- The AI Use Case Hub documents 73 real document automation deployments across 12 industries, with 60 detailed company examples you can browse.
- Which industries adopt document automation the most?
- Document automation is most common in Finance (38%), Insurance (15%) and Professional Services (8%).
- Which countries lead in document automation?
- United States leads documented document automation deployments, followed by India and United Kingdom.
- What technologies are used for document automation?
- Teams most often build document automation with Amazon Bedrock, Vertex AI and Azure OpenAI.
- What AI capabilities power document automation?
- Across the documented deployments, the most common capability patterns are Agent (22%), Vision (15%) and RAG (14%).
- What results do companies report from document automation?
- Across the 73 deployments reporting outcomes, companies most often cite speed & agility (68%), new product / capability (64%) and customer experience & trust (59%). Where impact is quantified, the strongest evidence is in time & speed: a median −60% across 13 reported metrics.