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The algorithmic trading market is projected to grow by USD 15.33 billion from 2024 to 2028, driven by rising demand for AI-powered market surveillance- Technavio

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NEW YORK, Sept. 6, 2024 /PRNewswire/ — Report on how AI is driving market transformation- The global algorithmic trading market size is estimated to grow by USD 15.32 billion from 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of  14.34%  during the forecast period. High demand for market surveillance is driving market growth, with a trend towards technological advancements. However, wider bid-ask spread in APAC  poses a challenge. Key market players include 63 Moons Technologies Ltd., AlgoBlocks, AlgoBulls Technologies Pvt. Ltd., AlpacaDB Inc., Argo SE, Auros, CRYPTO TECHFIN SL, InfoReach Inc., iRageCapital Advisory Pvt. Ltd., MetaQuotes Ltd., QuantConnect Corp., QuantCore Capital Management LLC, Refinitiv, Software AG, Symphony Fintech Solutions Pvt. Ltd., Tata Consultancy Services Ltd., Thomson Reuters Corp., uTrade, Virtu Financial Inc., and Wyden AG.

Key insights into market evolution with AI-powered analysis. Explore trends, segmentation, and growth drivers- View the snapshot of this report

Algorithmic Trading Market Scope

Report Coverage

Details

Base year

2023

Historic period

2018 – 2022

Forecast period

2024-2028

Growth momentum & CAGR

Accelerate at a CAGR of 14.34%

Market growth 2024-2028

USD 15326.2 million

Market structure

Fragmented

YoY growth 2022-2023 (%)

12.7

Regional analysis

North America, APAC, Europe, South America, and Middle East and Africa

Performing market contribution

APAC at 35%

Key countries

US, China, UK, Japan, and Germany

Key companies profiled

63 Moons Technologies Ltd., AlgoBlocks, AlgoBulls Technologies Pvt. Ltd., AlpacaDB Inc., Argo SE, Auros, CRYPTO TECHFIN SL, InfoReach Inc., iRageCapital Advisory Pvt. Ltd., MetaQuotes Ltd., QuantConnect Corp., QuantCore Capital Management LLC, Refinitiv, Software AG, Symphony Fintech Solutions Pvt. Ltd., Tata Consultancy Services Ltd., Thomson Reuters Corp., uTrade, Virtu Financial Inc., and Wyden AG

Market Driver

The introduction of advanced electronic trading technologies has significantly benefited both vendors and customers in the Algorithmic Trading Market. Liquidity aggregation and algorithmic trading across various geographies have expanded market access for participants, reducing risk sharing and resulting in lower trading costs and faster execution times. This has contributed to an increase in FX turnover. New liquidity aggregation methods, such as linking multiple investor pools through algorithms, have reduced search costs, a key feature of the OTC market. Financial institutions are prioritizing transparency in collateral availability, focusing on efficient decision-making and risk reduction in collateral transactions. They plan to invest heavily in collateral management during the forecast period, focusing on optimization, cheapest-to-deliver algorithms, and risk management, aiming to maximize profits and drive market growth. 

Algorithmic trading, also known as Algo trading, is the use of computer programs and mathematical algorithms to make trades in financial markets based on predefined rules. This automated approach is popular among hedge funds, institutional investors, pension funds, mutual funds, and other financial institutions. Algo trading involves the use of complex mathematical models to identify trends and make trades in stocks, bonds, currencies, commodities, and even cryptocurrencies. The trend towards algorithmic trading is driven by the need for speed and efficiency, as well as the desire to minimize human error. Algo trading platforms and professional services offer cloud-based deployment, making it accessible to large enterprises and capital markets firms. However, the use of black box trading and artificial intelligence (AI) raises concerns around market transparency, accountability, and market integrity. Risk management is a key consideration in algorithmic trading, particularly in volatile markets. Market volatility and price fluctuations can impact the performance of financial service algorithms, making risk management an essential component of any Algo trading strategy. Additionally, the use of cloud technologies and cloud-based trading solutions offers business agility and improved liquidity. Despite the benefits, there are challenges associated with Algo trading, including the risk of flash crashes and the need for risk management systems. As the trend towards automation continues, it is essential that market participants prioritize market transparency, accountability, and market integrity to ensure the long-term sustainability of financial markets. 

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Market Challenges

The algorithmic trading market in Asia Pacific (APAC) encounters challenges due to wider bid-ask spreads in various stocks. For instance, the average dealing spread in Singapore’s stocks is approximately 0.75%. Although market liquidity can be substantial, large spreads make trading difficult. Some stocks with high volatility and low turnover pose additional challenges for algorithmic trading. Nevertheless, industry players in APAC are exploring ways to replicate the success of algorithms in the US and Europe. The algorithmic trading market in APAC is still in its initial stages. Countries like China, Japan, Hong Kong, Singapore, and South Korea are leading the way. However, local players in APAC lag behind their counterparts in the Americas and Europe in terms of algorithmic trading strategies. This disparity is anticipated to impede the growth of the market in the forecast period.Algorithmic trading, also known as automated trading, is a method used by institutions and individuals to execute trades faster and more efficiently in the stock market and cryptocurrency market. However, it comes with challenges. Market volatility and price fluctuations can make it difficult for algorithms to make accurate predictions. Market transparency is essential for accountability, but maintaining it can be challenging. Speed and efficiency are key, but ensuring market integrity and preventing flash crashes requires careful consideration. Algorithmic trading platforms and professional services offer solutions, including cloud-based deployment for business agility and accessibility. Large enterprises, institutional investors, pension funds, and mutual funds use these tools. AI and financial service algorithms power automated trading, while matching engines ensure liquidity. Cloud technologies enable automated trading, including cloud-based solutions and hybrid cloud deployments. Blockchain adds security and transparency. Acquisitions and partnerships drive innovation, with workflow solutions, covert execution algorithms, and digital onboarding solutions among the offerings. Automated trading bots, volume, price, and time are essential factors. DoubleVerify ensures accuracy and reliability, while ensuring market integrity remains a top priority.

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Segment Overview 

This algorithmic trading market report extensively covers market segmentation by  

Component 1.1 Solutions1.2 ServicesEnd-user 2.1 Institutional investors2.2 Retail investors2.3 Long-term investors2.4 Short-term investorsGeography 3.1 North America3.2 APAC3.3 Europe3.4 South America3.5 Middle East and Africa

1.1 Solutions-  Algorithmic trading is a method of executing trades automatically based on predefined instructions. It uses complex mathematical models and algorithms to identify trading opportunities and execute trades at optimal prices. This automated approach allows for faster and more accurate trade executions, reducing human error and enhancing overall efficiency in financial markets. Algorithmic trading systems analyze market data in real-time and execute trades based on specific market conditions, providing an edge to traders in today’s fast-paced financial markets.

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Research Analysis

Algorithmic trading, also known as Algo trading, is the use of computer programs and mathematical algorithms to make trades in financial markets based on predefined rules. This automated approach to trading has become increasingly popular in various markets, including stocks, bonds, currencies, commodities, cryptocurrencies, and more. Algorithmic trading allows for faster execution, reduced human error, and the ability to process vast amounts of data in real-time. However, it also presents challenges such as market volatility, price fluctuations, and the need for risk management. Institutional investors, hedge funds, pension funds, mutual funds, and other financial entities use algorithmic trading to gain an edge in the markets. The use of artificial intelligence (AI) and financial service algorithms, as well as cloud-based solutions, is also becoming more prevalent in this field. Despite its benefits, algorithmic trading requires careful design, testing, and monitoring to ensure optimal performance and minimize potential risks.

Market Research Overview

Algorithmic trading, also known as Algo trading, is the use of computer programs and mathematical algorithms to make trades in financial markets based on predefined rules. This automated approach to trading is utilized in various markets, including stocks, bonds, currencies, commodities, and even cryptocurrencies. Algo trading offers several advantages such as speed, efficiency, accessibility, and reduced human error. However, it also presents challenges like market volatility, price fluctuations, and market transparency. Risk management is crucial in Algo trading, as large financial institutions, hedge funds, pension funds, mutual funds, and other institutional investors increasingly rely on this method for executing trades. Algorithmic trading platforms and professional services provide essential tools for these entities, offering cloud-based deployment, automated trading, matching engines, and other advanced features. Cloud technologies, artificial intelligence (AI), and financial service algorithms are driving the evolution of Algo trading, enabling business agility and improved market integrity. However, concerns over market transparency, accountability, and potential flash crashes continue to be addressed through regulatory measures and technological advancements. Key components of Algo trading include automated trading bots, volume, price, time, and various workflow solutions. As the market continues to evolve, we can expect further acquisitions, innovations, and advancements in this area.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

ComponentSolutionsServicesEnd-userInstitutional InvestorsRetail InvestorsLong-term InvestorsShort-term InvestorsGeographyNorth AmericaAPACEuropeSouth AmericaMiddle East And Africa

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio’s report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio’s comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/

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SOURCE Technavio

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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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