This put up is cowritten by Laura Skylaki, Vaibhav Goswami, Ramdev Wudali and Sahar El Khoury from Thomson Reuters.
Thomson Reuters (TR) is a number one AI and expertise firm devoted to delivering trusted content material and workflow automation options. With over 150 years of experience, TR gives important options throughout authorized, tax, accounting, threat, commerce, and media sectors in a fast-evolving world.
TR acknowledged early that AI adoption would essentially rework skilled work. Based on TR’s 2025 Way forward for Professionals Report, 80% of pros anticipate AI considerably impacting their work inside 5 years, with projected productiveness beneficial properties of as much as 12 hours per week by 2029. To unlock this immense potential, TR wanted an answer to democratize AI creation throughout its group.
On this weblog put up, we discover how TR addressed key enterprise use instances with Open Area, a extremely scalable and versatile no-code AI answer powered by Amazon Bedrock and different AWS companies reminiscent of Amazon OpenSearch Service, Amazon Easy Storage Service (Amazon S3), Amazon DynamoDB, and AWS Lambda. We’ll clarify how TR used AWS companies to construct this answer, together with how the structure was designed, the use instances it solves, and the enterprise profiles that use it. The system demonstrates TR’s profitable method of utilizing present TR companies for speedy launches whereas supporting hundreds of customers, showcasing how organizations can democratize AI entry and assist enterprise profiles (for instance, AI explorers and SMEs) to create purposes with out coding experience.
Introducing Open Area: No-code AI for all
TR launched Open Area to non-technical professionals to create their very own personalized AI options. With Open Area customers can use cutting-edge AI powered by Amazon Bedrock in a no-code atmosphere, exemplifying TR’s dedication to democratizing AI entry.
Right this moment, Open Area helps:
- Excessive adoption: ~70% worker adoption, with 19,000 month-to-month lively customers.
- Customized options: Hundreds of personalized AI options created with out coding, used for inner workflows or built-in into TR merchandise for patrons.
- Self-served performance: 100% self-served performance, in order that customers, regardless of technical background, can develop, consider, and deploy generative AI options.
The Open Area journey: From prototype to enterprise answer
Conceived as a speedy prototype, Open Area was developed in underneath six weeks on the onset of the generative AI growth in early 2023 by TR Labs – TR’s devoted utilized analysis division centered on the analysis, improvement, and utility of AI and rising developments in applied sciences. The aim was to assist inner staff exploration of enormous language fashions (LLMs) and uncover distinctive use instances by merging LLM capabilities with TR firm knowledge.
Open Area’s introduction considerably elevated AI consciousness, fostered developer-SME collaboration for groundbreaking ideas, and accelerated AI functionality improvement for TR merchandise. The speedy success and demand for brand new options rapidly highlighted Open Area’s potential for AI democratization, so TR developed an enterprise model of Open Area. Constructed on the TR AI Platform, Open Area enterprise model affords safe, scalable, and standardized companies protecting your entire AI improvement lifecycle, considerably accelerating time to manufacturing.
The Open Area enterprise model makes use of present system capabilities for enhanced knowledge entry controls, standardized service entry, and compliance with TR’s governance and moral requirements. This model launched self-served capabilities so that each consumer, regardless of their technical means, can create, consider, and deploy personalized AI options in a no-code atmosphere.
“The muse of the AI Platform has at all times been about empowerment; within the early days it was about empowering Knowledge Scientists however with the rise of Gen AI, the platform tailored and advanced on empowering customers of any background to leverage and create AI Options.”
– Maria Apazoglou, Head of AI Engineering, CoCounsel
As of July 2025, the TR Enterprise AI Platform consists of 15 companies spanning your entire AI improvement lifecycle and consumer personas. Open Area stays one among its hottest, serving 19,000 customers every month, with rising month-to-month utilization.
Addressing key enterprise AI challenges throughout consumer sorts
Utilizing the TR Enterprise AI Platform, Open Area helped hundreds of pros transition into utilizing generative AI. AI-powered innovation is now readily within the palms of everybody, not simply AI scientists.
Open Area efficiently addresses 4 crucial enterprise AI challenges:
- Enablement: Delivers AI answer constructing with constant LLM and repair supplier expertise and assist for numerous consumer personas, together with non-technical.
- Safety and high quality: Streamlines AI answer high quality monitoring utilizing analysis and monitoring companies, while complying with knowledge governance and ethics insurance policies.
- Velocity and reusability: Automates workflows and makes use of present AI options and prompts.
- Assets and price administration: Tracks and shows generative AI answer useful resource consumption, supporting transparency and effectivity.
The answer at the moment helps a number of AI experiences, together with tech assist, content material creation, coding help, knowledge extraction and evaluation, proof studying, undertaking administration, content material summarization, private improvement, translation, and downside fixing, catering to completely different consumer wants throughout the group.
Determine 1. Examples of Open Area use instances.
AI explorers use Open Area to hurry up day-to-day duties, reminiscent of summarizing paperwork, partaking in LLM chat, constructing customized workflows, and evaluating AI fashions. AI creators and Topic Matter Specialists (SMEs) use Open Area to construct customized AI workflows and experiences and to guage options with out requiring coding information. In the meantime, builders can develop and deploy new AI options at pace, coaching fashions, creating new AI expertise, and deploying AI capabilities.
Why Thomson Reuters chosen AWS for Open Area
TR strategically selected AWS as a main cloud supplier for Open Area primarily based on a number of crucial components:
- Complete AI/ML capabilities: Amazon Bedrock affords quick access to a alternative of high-performing basis fashions from main AI firms like AI21 Labs, Anthropic, Cohere, DeepSeek, Luma AI, Meta, Mistral AI, OpenAI, Qwen, Stability AI, TwelveLabs, Author, and Amazon. It helps easy chat and complicated RAG workflows, and integrates seamlessly with TR’s present Enterprise AI Platform.
- Enterprise-grade safety and governance: Superior safety controls, mannequin entry utilizing RBAC, knowledge dealing with with enhanced security measures, single sign-on (SSO) enabled, and clear operational and consumer knowledge separation throughout AWS accounts.
- Scalable infrastructure: Serverless structure for automated scaling, pay-per-use pricing for value optimization, and international availability with low latency.
- Current relationship and experience: Sturdy, established relationship between TR and AWS, present Enterprise AI Platform on AWS, and deep AWS experience inside TR’s technical groups.
“Our long-standing partnership with AWS and their strong, versatile and revolutionary companies made them the pure option to energy Open Area and speed up our AI initiatives.”
– Maria Apazoglou, Head of AI Engineering, CoCounsel
Open Area structure: Scalability, extensibility, and safety
Designed for a broad enterprise viewers, Open Area prioritizes scalability, extensibility and safety whereas sustaining simplicity for non-technical customers to create and deploy AI options. The next diagram illustrates the structure of Open Area.
Determine 2. Structure design of Open Area.
The structure design facilitates enterprise-grade efficiency with clear separation between functionality and utilization, aligning with TR’s enterprise value and utilization monitoring necessities.
The next are key elements of the answer structure:
- No-code interface: Intuitive UI, visible workflow builder, pre-built templates, drag-and-drop performance.
- Enterprise integration: Seamless integration with TR’s Enterprise AI Platform, SSO enabled, knowledge dealing with with enhanced safety, clear knowledge separation.
- Answer administration: Searchable repository, public/non-public sharing, model management, utilization analytics.
TR developed Open Area utilizing AWS companies reminiscent of Amazon Bedrock, Amazon OpenSearch, Amazon DynamoDB, Amazon API Gateway, AWS Lambda, and AWS Step Capabilities. It makes use of Amazon Bedrock for foundational mannequin interactions, supporting easy chat and complicated Retrieval-Augmented Era (RAG) duties. Open Area makes use of Amazon Bedrock Flows because the customized workflow builder the place customers can drag-and-drop elements like prompts, brokers, information bases and Lambda capabilities to create subtle AI workflows with out coding. The system additionally integrates with AWS OpenSearch for information bases and exterior APIs for superior agent capabilities.
For knowledge separation, orchestration is managed utilizing the Enterprise AI Platform AWS account, capturing operational knowledge. Move situations and user-specific knowledge reside within the consumer’s devoted AWS account, saved in a database. Every consumer’s knowledge and workflow executions are remoted inside their respective AWS accounts, which is required for complying with Thomson Reuters knowledge sovereignty and enterprise safety insurance policies with strict regional controls. The system integrates with Thomson Reuters SSO answer to mechanically establish customers and grant safe, non-public entry to foundational fashions.
The orchestration layer, centrally hosted throughout the Enterprise AI Platform AWS account, manages AI workflow actions, together with scheduling, deployment, useful resource provisioning, and governance throughout consumer environments.
The system options totally automated provisioning of Amazon Bedrock Flows instantly inside every consumer’s AWS account, avoiding guide setup and accelerating time to worth. Utilizing AWS Lambda for serverless compute and DynamoDB for scalable, low-latency storage, the system dynamically allocates sources primarily based on real-time demand. This structure makes positive immediate flows and supporting infrastructure are deployed and scaled to match workload fluctuations, optimizing efficiency, value, and consumer expertise.
“Our choice to undertake a cross-account structure was pushed by a dedication to enterprise safety and operational excellence. By isolating orchestration from execution, we be sure that every consumer’s knowledge stays non-public and safe inside their very own AWS account, whereas nonetheless delivering a seamless, centrally-managed expertise. This design empowers organizations to innovate quickly with out compromising compliance or management.”
– Thomson Reuters’ structure staff
Evolution of Open Area: From basic to Amazon Bedrock Flows-powered chain builder
Open Area has advanced to cater to various ranges of consumer sophistication:
- Open Area v1 (Traditional): Encompasses a form-based interface for easy immediate customization and fundamental AI workflow deployment inside a single AWS account. Its simplicity appeals to novice customers for easy use instances, although with restricted superior capabilities.
- Open Area v2 (Chain Builder): Introduces a sturdy, visible workflow builder interface, enabling customers to design complicated, multi-step AI workflows utilizing drag-and-drop elements. With assist for superior node sorts, parallel execution, and seamless cross-account deployment, Chain Builder dramatically expands the system’s capabilities and accessibility for non-technical customers.
Thomson Reuters makes use of Amazon Bedrock Flows as a core characteristic of Chain Builder. Customers can outline, customise, and deploy AI-driven workflows utilizing Amazon Bedrock fashions. Bedrock Flows helps superior workflows combining a number of immediate nodes, incorporating AWS Lambda capabilities, and supporting subtle RAG pipelines. Working seamlessly throughout consumer AWS accounts, Bedrock Flows facilitates safe, scalable execution of customized AI options, serving as the basic engine for the Chain Builder workflows and driving TR’s means to ship strong, enterprise-grade automation and innovation.
What’s subsequent?
TR continues to increase Open Area’s capabilities via the strategic partnership with AWS, specializing in:
- Driving additional adoption of Open Area’s DIY capabilities.
- Enhancing flexibility for workflow creation in Chain Builder with customized elements, reminiscent of inline scripts.
- Growing new templates to signify widespread duties and workflows.
- Enhancing collaboration options inside Open Area.
- Extending multimodal capabilities and mannequin integration.
- Increasing into new use instances throughout the enterprise.
“From innovating new product concepts to reimagining every day duties for Thomson Reuters workers, we proceed to push the boundaries of what’s potential with Open Area.”
– Maria Apazoglou, Head of AI Engineering, CoCounsel
Conclusion
On this weblog put up, we explored how Thomson Reuters’ Open Area demonstrates the profitable democratization of AI throughout an enterprise through the use of AWS companies, significantly Amazon Bedrock and Bedrock Flows. With 19,000 month-to-month lively customers and 70% worker adoption, the system proves that no-code AI options can ship enterprise-scale impression whereas sustaining safety and governance requirements.
By combining the strong infrastructure of AWS with revolutionary structure design, TR has created a blueprint for AI democratization that empowers professionals throughout technical ability ranges to harness generative AI for his or her every day work.
As Open Area continues to evolve, it exemplifies how strategic cloud partnerships can speed up AI adoption and rework how organizations method innovation with generative AI.
In regards to the authors
Laura Skylaki, PhD, leads the Enterprise AI Platform at Thomson Reuters, driving the event of GenAI companies that speed up the creation, testing and deployment of AI options, enhancing product worth. A acknowledged professional with a doctorate in stem cell bioinformatics, her intensive expertise in AI analysis and sensible utility spans authorized, tax, and biotech domains. Her machine studying work is revealed in main educational journals, and he or she is a frequent speaker on AI and machine studying
Vaibhav Goswami is a Lead Software program Engineer on the AI Platform staff at Thomson Reuters, the place he leads the event of the Generative AI Platform that empowers customers to construct and deploy generative AI options at scale. With experience in constructing production-grade AI methods, he focuses on creating instruments and infrastructure that democratize entry to cutting-edge AI capabilities throughout the enterprise.
Ramdev Wudali is a Distinguished Engineer, serving to architect and construct the AI/ML Platform to allow the Enterprise consumer, knowledge scientists and researchers to develop Generative AI and machine studying options by democratizing entry to instruments and LLMs. In his spare time, he likes to fold paper to create origami tessellations, and sporting irreverent T-shirts
Because the director of AI Platform Adoption and Coaching, Sahar El Khoury guides customers to seamlessly onboard and efficiently use the platform companies, drawing on her expertise in AI and knowledge evaluation throughout robotics (PhD), monetary markets, and media.
Vu San Ha Huynh is a Options Architect at AWS with a PhD in Laptop Science. He helps massive Enterprise prospects drive innovation throughout completely different domains with a concentrate on AI/ML and Generative AI options.
Paul Wright is a Senior Technical Account Supervisor, with over 20 years expertise within the IT business and over 7 years of devoted cloud focus. Paul has helped a number of the largest enterprise prospects develop their enterprise and enhance their operational excellence. In his spare time Paul is a big soccer and NFL fan.
Mike Bezak is a Senior Technical Account Supervisor in AWS Enterprise Help. He has over 20 years of expertise in data expertise, primarily catastrophe restoration and methods administration. Mike’s present focus helps prospects streamline and optimize their AWS Cloud journey. Exterior of AWS, Mike enjoys spending time with household & buddies.
