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Neo4j Launches Industry’s First Graph Analytics Offering For Any Data Platform

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1 year ago

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Serverless offering with 65+ ready-to-use algorithms boosts model accuracy by up to 80% and delivers 2X deeper insights – no graph expertise needed

SAN MATEO, Calif. , May 7, 2025 /PRNewswire/ — Neo4j®, the world’s leading graph database and analytics company, announced the launch of Neo4j Aura Graph Analytics, a new serverless offering that for the first time can be used seamlessly with any data source, and with Zero ETL (extract, load, transfer). The solution delivers the power of graph analytics to users of all skill levels, unlocking deeper intelligence and achieving 2X* greater insight precision and quality over traditional analytics. Neo4j Aura Graph Analytics is generally available now on a pay-as-you-use basis and works with all databases, such as Oracle and Microsoft SQL, all cloud data warehouses and data lake platforms, such as Databricks, Snowflake, Google BigQuery, Microsoft OneLake, and on any cloud.

Graph analytics improves AI decision-making by uncovering hidden patterns and relationships in complex data, delivering more accurate insights with richer context than traditional analytics. Yet despite its powerful capabilities, graph analytics has remained out of reach for many organizations due to its complexity and learning curve – until now. The new Neo4j offering makes graph analytics capabilities accessible to everyone and eliminates adoption barriers by removing the need for custom queries, ETL pipelines, or any need for specialized graph expertise – so that business decision-makers, data scientists, and other users can focus on outcomes, not overhead.

“Data captured in any enterprise is sparse and replete with gaps, making it difficult to find and link useful data. Data and analytics leaders should use graph analytics as a preferred technology in specific use cases to fill data gaps and blend data assets even when they have diverse data quality,” says Gartner in its Exploring the Top Use Cases for Graph Analytics report, May 10, 2024, by Jim Hare and Mark Beyer.

Neo4j Aura Graph Analytics requires no infrastructure setup and no prior experience with graph technology or Cypher query language. Users seamlessly deploy and scale graph analytics workloads end-to-end, enabling them to collect, organize, analyze, and visualize data. The offering includes the industry’s largest selection of 65+ ready-to-use graph algorithms and is optimized for high-performance applications and parallel workflows. Users pay only for the processing power and storage they consume.

Additional benefits and capabilities below are based on customer-reported outcomes that reflect real-world performance gains:

Up to 80% model accuracy, leading to 2X greater efficacy of insights that go beyond the limits of traditional analytics. Accuracy is achieved by transforming graph structures into ML-ready features with graph embeddings, unlocking graph’s unique ability to uncover deeper patterns and relationships in complex connected data. Graph also dynamically aligns in real time as data changes, because it is driven by the connections between data points, not just the data itself. Advanced graph algorithms and embeddings, such as centrality, pathfinding, community detection, link prediction, and similarity, dramatically improve outcomes across hundreds of use cases such as fraud detection, anti-money laundering, disease contact tracing, customer 360, supply chain management, recommendation engines, and social network analysis.Insights achieved twice as fast as open-source alternatives with parallelized in-memory processing of graph algorithms. The offering’s ability to run different yet simultaneous DSML (data science and machine learning) research instances also improves data analyst productivity. Users can scale graph analytics across their organization with unlimited concurrent sessions, each running independently.75% less code, Zero ETL. Lower code is achieved by the ability to apply 65+ ready-to-use graph algorithms, eliminating the need to manually build models for each analysis. Users run the offering anywhere, directly on any enterprise data and in the data science environment most familiar to them by easily projecting data from Pandas dataframes, and with Zero-ETL. Users are also able to use the Python-based data science tools that they are already familiar with to project subgraphs, run algorithms, and return results.No administration overhead, and lower total cost of ownership. The fully managed serverless offering removes the burden of server provisioning, maintenance, or resource management. Users also minimize administrative costs and optimize infrastructure costs through a flexible pay-as-you-use service, scaling compute and storage up or down as needed for more precise spending control.

Neo4j Aura Graph Analytics is available for all data sources through Pandas dataframes in Python. According to GitHub, Python is the most commonly used language for AI. Support for all other major languages is expected this year.

Native integration with Snowflake to be generally available by Q3FY25

Neo4j Graph Analytics for Snowflake, a native integration with Snowflake, will be generally available this Q3 following its launch last year and numerous large-scale enterprise deployments. The move underscores mainstream demand for graph analytics across the most widely adopted data clouds, so that organizations across industries can operationalize data for faster and more accurate insights regardless of where that data lives. The offering can be purchased on Snowflake Marketplace.

Latest milestones driven by surging AI and graph demand

Neo4j’s new serverless offering builds on a series of milestones for Neo4j. In September 2024, Neo4j transformed its Aura cloud database management system portfolio with AI-ready capabilities to simplify and accelerate graph adoption across any use case or workload. The result enabled Neo4j to advance its position as the category leader and the preferred graph partner across all major cloud service providers due to its comprehensive offering, deployment flexibility, analytics, and strong community support, accelerated with GenAI.

In December, the company was recognized as a Visionary in the 2024 Gartner® Magic Quadrant™ for Cloud Database Management Systems for the second consecutive year. Neo4j also ranked as a Strong Performer among 14 top vendors in The Forrester Wave™: Vector Databases, Q3 2024.

In November 2024, Neo4j doubled its annual recurring revenue in three years at a $2B+ valuation, driven by growing cloud adoption and GenAI demand. Neo4j is used by 84% of Fortune 100 companies and 58% of the Fortune 500, including Adobe, BT Group, Novo Nordisk, and UBS.

Visit our website and blog for more details.

Supporting quotes

Dor Shoef, Data Engineering Tech Lead, Resident Home
“At Resident Home, our e-commerce results are driven by real-time, accurate data. To achieve that, we moved to AuraDB with serverless graph analytics capabilities, given its combination of reliability, high availability, and powerful advanced algorithms. It was quick and easy: in less than a few hours, we were able to make the switch in our code and get it up and running. We could also scale up our graph analytics memory on-demand, for even faster results without touching the main instance’s configurations.”

Benjamin Squire, Principal Data Scientist, Audience Acuity
“Audience Acuity was founded to solve complex identity-resolution challenges. Our approach using Neo4j Graph Analytics for Snowflake ensures marketers stay ahead of the curve by stitching together records from 20 distinct data sources —encompassing 2.2 billion records— using SQL without ever moving the data. Neo4j’s graph-powered algorithms provided advanced insights offering a transformative edge over traditional methods.”

Devin Pratt, Research Director, Data Management, IDC
“Neo4j’s new serverless graph analytics solution, developed with ease-of-use and accessibility in mind, is an exciting move that will allow enterprises to scale analytics across any data source or cloud platform, transforming their data into a wealth of actionable knowledge and providing deeper insights for improved organizational decision-making.”

Sudhir Hasbe, Chief Product Officer, Neo4j
“Our vision with Aura Graph Analytics is simple: make it easy for any user to make better business decisions faster. By removing hurdles like complex queries, ETL, and costly infrastructure set-up, organizations can tap into the full power of graph analytics without needing to be graph experts. The result: better decisions on any enterprise data source, built on a deeper understanding of how everything connects.”

*According to customer benchmark data, Neo4j Aura Graph Analytics provides 50-80% greater accuracy in DS/ML models over traditional non-graph analytics models, resulting in 2x improvement in overall efficacy of their insights.

Attributions and Disclaimers
Gartner, Gartner® Magic Quadrant™ for Cloud Database Management Systems, Henry Cook, Ramke Ramakrishnan, Xingyu Gu, Aaron Rosenbaum, Masud Miraz, December 18, 2024.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved. 
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

About Neo4j
Neo4j, the Graph Database & Analytics leader, helps organizations find hidden patterns and relationships across billions of data connections deeply, easily, and quickly. Customers leverage the structure of their connected data to reveal new ways of solving their most pressing business problems, from fraud detection, customer 360, knowledge graphs, supply chain, personalization, IoT, network management, and more – even as their data grows. Neo4j’s full graph stack delivers powerful native graph storage with native vector search capability, data science, advanced analytics, and visualization, with enterprise-grade security controls, scalable architecture, and ACID compliance. Neo4j’s dynamic open-source community brings together over 250,000 developers, data scientists, and architects across hundreds of Fortune 500 companies, government agencies, and NGOs. Visit neo4j.com.

Contact:
pr@neo4j.com
neo4j.com/pr

©2025 Neo4j, Inc., Neo Technology®, Neo4j®, Cypher®, Neo4j Bloom™, Neo4j Graph Data Science Library™, Neo4j® Aura™, and Neo4j® AuraDB™ are registered trademarks or a trademark of Neo4j, Inc. All other marks are owned by their respective companies.

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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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47 minutes ago

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October 21, 2026

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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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47 minutes ago

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October 21, 2026

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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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47 minutes ago

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October 21, 2026

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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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