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TwelveLabs to Bring Its State-of-the-Art Video AI Models to Amazon Bedrock

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Latest collaboration enables developers to leverage TwelveLabs’ video understanding capabilities to create new applications with the security, privacy, and performance of AWS

LAS VEGAS, April 6, 2025 /PRNewswire/ — Amazon Web Services (AWS), an Amazon.com, Inc. company and TwelveLabs, the video understanding company, today announced that TwelveLabs’ state-of-the-art multimodal foundation models, Marengo and Pegasus, will soon be available in Amazon Bedrock. Amazon Bedrock is a fully managed service that offers developers access to high-performing models from leading AI companies through a single API. Seamless access to TwelveLabs’ advanced video understanding capabilities will enable developers and enterprises to transform how they search, analyze, and generate insights from video content, leveraging the security, privacy, and performance of AWS. AWS is the first cloud provider to offer models from TwelveLabs.

“This integration with Amazon Bedrock represents the next phase in our collaboration with AWS, making our video understanding AI more accessible to enterprises worldwide,” added Lee.

“Video contains nearly 80% of the world’s data, yet most of it remains unsearchable and underutilized,” said Jae Lee, Co-founder and CEO of TwelveLabs. “By making our models available through Amazon Bedrock, we’re empowering even more enterprises to bring video understanding to their existing infrastructure. Our technology enables users to search across their entire content library—from videos collected 10 years ago or 10 minutes ago—to find the precise moment they’re looking for in less than a single second, and then interpret and analyze those moments. This opens the door for all kinds of novel uses. Through the collaboration with AWS, we can extend powerful capabilities to customers and accelerate innovation across industries.”

Advanced AI Video Capabilities

Video is commonly regarded as one of the world’s largest unsearchable data sources, yet TwelveLabs’ cutting-edge technology turns it into a trove of accessible information. Whether it’s giving a sports network the ability to instantly pull every instance of a specific play style or commentator reaction or helping a broadcaster identify recurring themes across large volumes of footage, TwelveLabs helps teams turn their video archives into usable, indexable assets, unlocking both operational efficiency and new revenue opportunities.

TwelveLabs overcomes the inherent complexities associated with video understanding to allow customers to search video across all modalities. Specifically, TwelveLabs delivers:

Natural language video search that pinpoints precise content momentsDeep video understanding without requiring pre-defined labelsMultimodal AI processing visual, audio, and text simultaneouslyTemporal intelligence connecting related events across timeEnterprise solutions scaling extensive video libraries into accessible knowledge

“At MLSE, we are defining the future of the sports and entertainment business. Innovation is in our DNA, and we’re leading the charge in shaping what comes next. With powerful tools like Amazon Bedrock and TwelveLabs’ AI models supporting our vision, we’re accelerating our ability to create smarter, more immersive experiences for fans.” said Humza Teherany, Chief Strategy and Innovation Officer at Maple Leaf Sports & Entertainment.”

Unlocking the Power of Video Understanding for AWS Customers

With Marengo and Pegasus available in Amazon Bedrock, AWS customers can use TwelveLabs’ models to build and scale generative AI applications without managing underlying infrastructure. Using Amazon Bedrock, customers gain access to a broad set of capabilities while maintaining complete control over their data, benefiting from enterprise-grade security and utilizing cost control features—all essential for deploying AI responsibly at scale.

TwelveLabs’ fully managed, serverless models in Amazon Bedrock allow developers to:

Create applications that search through videos, classify scenes, summarize content, and extract insights using natural languageBuild sophisticated video understanding features without specialized AI expertiseScale video processing from small collections to massive libraries with consistent performanceDeploy solutions with enterprise-grade security and governance controls

“Video understanding is revolutionizing how industries like media & entertainment, sports, automotive, and education work with and discover content,” said Samira Panah Bakhtiar, General Manager of Media & Entertainment, Games, and Sports at AWS. “Over the last year, I have consistently said that natural language semantic search is a ‘strategic unlock’ for our entertainment customers, as they reexamine their existing intellectual property and breathe new life into it. By bringing TwelveLabs’ advanced models to Amazon Bedrock, we’re helping our customers make sense of any video moment, unlocking the full value of their treasured video assets. Businesses will now be able to easily search, categorize, and extract insights from their vast video libraries, enabling new use cases and better user experiences that were previously impossible without significant technical expertise.”

The integration will benefit multiple industries, from media, entertainment, advertising and beyond. For example:

Film and TV Studios can rapidly manage video workloads from dailies, content repacking, and archive managementSports Leagues and Teams can efficiently create match highlights and create customized fan focused content at scaleNews Agencies and Broadcasters can quickly manage large libraries to find the moments that matterStreaming services can better package and distribute content across platforms and more effectively insert relevant video ads

AWS and TwelveLabs’ integration partner Monks expressed their excitement: “We’ve been putting AI to work across the entire video value chain for IP holders, broadcasters and brands. TwelveLabs in Amazon Bedrock makes it easier to realize opportunities for monetization in broadcast news, entertainment and sports by making it simpler and more secure to build and scale applications with powerful video understanding,” said Lewis Smithingham, EVP Strategic Industries at Monks.

Expanding Collaboration Between AWS and TwelveLabs

This announcement builds on a strong existing relationship between AWS and TwelveLabs and continues the momentum of their Strategic Collaboration Agreement (SCA). TwelveLabs is working with AWS to accelerate the development of its foundation models, deploy its advanced video understanding foundation models across new industries, and enhance its model training capabilities using Amazon SageMaker HyperPod. With the reliable and scalable infrastructure offered by SageMaker HyperPod, TwelveLabs has accelerated model training while reducing training costs.

“This integration with Amazon Bedrock represents the next phase in our collaboration with AWS, making our video understanding AI more accessible to enterprises worldwide,” added Lee.

To learn about TwelveLabs’ industry leading models, please explore twelvelabs.io, Marengo 2.7 and Pegasus 1.2. Find out more about TwelveLabs models in Amazon Bedrock here.

About TwelveLabs

TwelveLabs uses multimodal foundation models to bring human-like understanding to video data. The company’s foundation models map natural language to what’s happening inside a video, including actions, objects, and background sounds, allowing developers to create applications that can search through videos, classify scenes, summarize, and extract insights with unprecedented accuracy. Headquartered in the US, TwelveLabs serves customers across media, entertainment, sports, advertising, and government. For more information, visit www.twelvelabs.io

Media Contact

Amber Moore, Moore Communications, 1 5039439381, amber@moorecom2.com, Moore Communications

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SOURCE TwelveLabs

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Toku launches Makimoto Flows, a visual builder for speech AI pipelines, taking its open-source initiative beyond transcription

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Developers can chain transcription, summarisation and call tagging on one canvas, test each step and export the pipeline as code, with every step processed in Singapore

SINGAPORE, Oct. 21, 2026 /PRNewswire/ — Toku Ltd. (SGX: TKU), a Singapore-headquartered AI-powered customer experience (CX) platform, has launched Makimoto Flows (“Flows”), a visual builder within its open-source conversational AI initiative where developers assemble speech AI pipelines block by block and test each stage on a recorded call. Flows is now live at makimoto.ai.

On the Flows canvas, developers connect blocks to build a speech AI pipeline and test each step individually. The Transcribe block converts audio into text using Kawa, the Summarise block generates a topic and short summary from the transcript, and the Tags block classifies each call across seven categories, including customer sentiment. Developers can see how audio moves from transcription to analysis, and control how each stage connects and runs. Every block runs in Singapore, so audio, transcripts and the resulting analysis stay in-country.

The Chained Analysis starter template puts these blocks together in one click, and developers can adjust any block and rerun it to compare results. Each block maps to a Makimoto API endpoint, and any flow can be exported as ready-to-run Python code, so developers can take the same capabilities into their own code for applications such as call recaps and call triage.

“Developers should have control over how their voice AI works, from the models they use to the way each stage connects. That is the principle behind Makimoto. Flows puts the orchestration layer in front of them: they can build a pipeline, run a recorded call through it and see what each step produces before anything reaches their customers. Models will keep changing. The ability to compose them, and to know where they run, is what lasts,” said Thomas Laboulle, Founder and CEO at Toku.

Flows builds on the composable architecture Toku set out when it introduced Makimoto in April 2026, and takes the initiative beyond transcription. Kawa, released on schedule on 1 July 2026, established the transcription layer through a Singapore-hosted API; summarisation and tagging endpoints followed in September; Flows now lets developers compose them visually. Next, Makimoto plans to add audio preparation blocks, starting with noise filtering, giving developers more control over how recordings are processed before transcription.

By pairing open-source development with enterprise-grade deployment, Makimoto complements Toku’s existing customer experience platform and supports long-term innovation opportunities across the Group’s AI roadmap.

Developers can create a free account at makimoto.ai, open the Chained Analysis template and run a sample recording, or one of their own call recordings, through it; each account includes 1,000 free minutes. Feedback reaches the Makimoto team directly from the portal.

About Toku

Headquartered in Singapore, Toku Ltd. (SGX Catalist: TKU) is a cloud-native, AI-powered customer experience platform purpose-built for enterprises operating in complex, multi-market environments. With deep roots in the APAC region and an expanding global footprint, Toku’s modular 360° CX Platform orchestrates customer interactions across voice, chat, email and digital channels while managing regulatory, linguistic and infrastructure complexity at scale.

Built on end-to-end ownership of its technology stack, from carrier-grade connectivity to AI applications, Toku delivers enterprise-grade security, reliability and deployment flexibility in commercial cloud, private data centres and hybrid environments. Its AI capabilities include transcription, summarisation, sentiment analysis, conversation analytics and governed virtual agents, designed to integrate seamlessly with enterprise systems and customer data.

Trusted by leading enterprises and public-sector organisations, Toku helps organisations streamline operations, scale customer engagement and deliver consistent experiences in fragmented markets worldwide.

For more information about Toku, visit toku.co.

About Makimoto

Makimoto is Toku’s open-source initiative, operated through Makimoto Technology Pte Ltd, a wholly owned subsidiary of the Toku Group, dedicated to building composable conversational AI infrastructure for Asia-Pacific. Its releases include Makimoto Kawa, a Singapore-hosted transcription API; summarisation and tagging endpoints; and Makimoto Flows, a visual builder for composing speech AI pipelines. For more information about Makimoto, visit makimoto.ai.

Forward-Looking Statements

This press release contains forward-looking statements regarding Toku’s expansion plans, business strategy and planned product releases. These statements are based on current expectations and assumptions and are subject to risks and uncertainties that could cause actual results to differ materially. Toku undertakes no obligation to update these statements to reflect subsequent events or circumstances.

Sponsor’s Statement

Toku Ltd. (the “Company”) was listed on Catalist of the Singapore Exchange Securities Trading Limited (the “Exchange”) on 22 January 2026. The initial public offering of the Company was sponsored by PrimePartners Corporate Finance Pte. Ltd. (the “Sponsor”). This press release has been reviewed by the Sponsor. It has not been examined or approved by the Exchange and the Exchange assumes no responsibility for the contents of this press release, including the correctness of any of the statements or opinions made or reports contained in this press release. The contact person for the Sponsor is Ms. Ng Shi Qing, 16 Collyer Quay, #10-00 Collyer Quay Centre, Singapore 049318, sponsorship@ppcf.com.sg.

Investor Relations Contact:
investor.relations@toku.co

Developers and Partners:
contact@makimoto.ai  

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SOURCE Toku Ltd.

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Conscious Spark LLC Launches Alphimiya® Neuro-Recalibration Framework Designed to Resolve C-Suite Revenue Plateaus

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New research-backed neuro-recalibration framework targets the autonomic nervous system’s threat response to managing high financial amounts, offering enterprise leaders a biological pathway to scaling.

ANTALYA, Turkey and ALBUQUERQUE, N.M., Oct. 21, 2026 /PRNewswire/ — Conscious Spark LLC, a research and advisory firm specializing in applied neuroscience for executive leadership, today announced the official launch of Alphimiya®, a proprietary C-suite neuro-recalibration framework designed to resolve corporate revenue plateaus by upgrading the biological capacity of enterprise decision-makers.

Developed to address the root causes of stalled enterprise growth, the Alphimiya® framework targets the human autonomic nervous system’s subconscious threat response to managing high financial amounts. When commercial leaders and CEOs attempt to scale past historical capital thresholds without recalibrating their stress response, the body’s natural survival mechanism triggers decision fatigue, strategic risk aversion, and systemic self-sabotage. Alphimiya® recalibrates this biological safety brake, enabling executive teams to hold, absorb, and scale larger financial volumes without physiological or operational friction.

“A corporate revenue plateau is rarely an operational or marketing failure; it is a biological safety brake embedded within executive leadership,” stated Dr. Ahmed Al-Nashi, Founder of Conscious Spark LLC. “When managing high financial amounts triggers an underlying physical stress response, the enterprise subconsciously contracts to remain in its perceived safe zone. Alphimiya® removes that biological friction, allowing C-level leaders to multiply revenue with calm, biological authority.”

The Alphimiya® framework restructures executive performance across three core operational pillars:

Sovereign Enterprise Scaling: Expands the nervous system’s tolerance for high-stakes capital, allowing leadership teams to scale revenue without experiencing executive burnout.

High-Value Deal Execution: Regulates autonomic stress responses during multi-million-dollar negotiations and volatile market entries, eliminating hesitation under pressure.

Restored Strategic Clarity: Removes chronic decision fatigue across C-suite teams, restoring mental focus and strategic presence inside and outside the boardroom.

By recalibrating the autonomic nervous system’s response to high capital exposure, Alphimiya® removes the subconscious biological brakes that lock corporate revenue at a standstill. Senior C-level executives and enterprise leadership teams seeking to evaluate their organization’s biological capacity can access the official executive briefing, case studies, and framework assessment directly at https://alphimiya.co/.

About Conscious Spark LLC

Conscious Spark LLC is a U.S.-registered firm specializing in executive education, training, and strategic performance consulting. Pioneering applied neuroscience for C-level leaders, founders, and commercial decision-makers, the firm utilizes its proprietary Alphimiya® methodology to enable leadership teams to recalibrate biological stress responses, resolve revenue ceilings, and build scalable corporations.

Media Relations Team
Conscious Spark LLC
Email: hello@consciousspark.online 
Website: https://alphimiya.co/

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SOURCE Conscious Spark LLC

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Daffodil Software Brings Multilingual Conversational AI to Aadhaar’s Udai Mascot

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GURUGRAM, India, Oct. 21, 2026 /PRNewswire/ — Daffodil Software showcased an AI-powered conversational experience featuring UIDAI’s Udai mascot at Aadhaar Samvaad 2026. Developed by Daffodil Software, the assistant is designed to help users access Aadhaar-related information through natural conversation, using official UIDAI as its reference knowledge base.

Daffodil Software has developed Udai, an AI-powered virtual mascot that helps users get clear, reliable answers about Aadhaar simply by talking to it. The assistant was showcased at Aadhaar Samvaad 2026, held in Kolkata on 29 September, coinciding with the 17th Aadhaar Day, where visitors watched it listen, respond, and gesture in real time in their own language.

For most people, questions about Aadhaar come up in daily life, and they usually need answers fast. Which documents do I need for an address change? How much does an update cost? How do I link Aadhaar to my bank account or mobile number? The answers exist, but finding them usually means working through long help pages and documents.

 Udai is designed to answer exactly these questions in a natural conversation, without anyone having to search through long help pages.

A conversation in the user’s own language

Udai speaks and understands 11 languages: Hindi, Tamil, Bengali, Telugu, Kannada, Malayalam, Marathi, Gujarati, Punjabi, Odia, and English. A user simply asks a question. Udai listens, works out the answer, and replies in the same language, with natural speech, matching lip movements and expressive hand gestures.

What sets Udai apart is how it is built. AI avatars rely on expensive, specialised graphics hardware to bring a face to life. Udai takes a simpler route. The character is created from pre-filmed footage, and its lip movements are matched to its speech in real time using lightweight processing that runs in a web browser.

The result is a smooth experience at 24 frames per second on ordinary servers, at a fraction of the usual cost per user. For a programme that serves hundreds of millions of people, that efficiency is what turns a nationwide rollout from an ambition into a practical plan.

“Our focus with Udai was to make Aadhaar-related information easier to access through natural conversation. Combining multilingual voice interaction with official reference content allowed our team to build an experience that is practical, approachable, and useful to users,” said Yogesh Agarwal, Founder and CEO, Daffodil Software.

Answers drawn only from official sources

The assistant uses official UIDAI material as its reference knowledge base: frequently asked questions, provisions of the Aadhaar Act, and government policy documents on Aadhaar services. It covers the topics users ask about most:

Enrolment and registrationAddress and demographic updatesFees, required documents and eligibilityeKYC and Virtual IDLinking Aadhaar with bank accounts, PAN and mobile numbersmAadhaar servicesGrievance redressal

Users don’t need to phrase their questions in any particular way. Udai understands everyday language, whether a question is spoken in English, Hindi, or asked in a mix of both, and finds the most relevant official information to answer it.

Built to be accurate, respectful, and secure

When a public service speaks directly to users, trust matters as much as convenience. Udai is protected by three layers of safeguards.

Accuracy first. Udai answers only from its verified knowledge base. Responses are grounded in a curated knowledge base of official UIDAI material. If a question falls outside Aadhaar, it guides the user back rather than offering an answer it cannot stand behind.

Respectful conversations. A screening layer catches abusive or offensive language in English, Hindi, and Hinglish before it reaches the assistant. Screening is designed to identify abusive language while supporting legitimate queries

Protection against misuse. Udai cannot be talked into abandoning its role, pretending to be someone else, revealing its internal setup, or answering beyond its approved scope. These checks work almost instantly, so users experience no delay.

What comes next?

Udai is planned to roll out in two phases.

In the first phase, the mascot will be placed in Aadhaar Centres. Visitors will be able to check information and understand processes on their own, such as which documents they need for an address change. This frees centre staff to focus on their core work instead of answering the same questions again and again.

In the second phase, Udai will come to the Aadhaar website and mobile app, taking the place of the current text-based chatbot, which was also built by Daffodil.

About Daffodil Software

Daffodil Software is a software engineering and AI solutions company serving businesses across industries. Its services span software consulting, product engineering, UI/UX design, AI/ML development, quality assurance, cloud and DevOps, and maintenance. The company serves sectors including healthcare, fintech, banking, technology, and digital commerce. Its client portfolio includes organizations such as the Reserve Bank of India, Mount Sinai Hospital, Maruti, Samsung, Pramerica Insurance, and Dangote Group. Daffodil Software has also been featured in industry research and recognition by Gartner, Everest Group, Zinnov, and Frost & Sullivan. For more information, visit https://www.daffodilsw.com

Media contact

Kunwar Pal Singh
media-relations@daffodilsw.com

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