Sphere

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About
Sphere is a sophisticated AI-driven investment platform developed by MDOTM Ltd, specifically engineered to support institutional investors such as asset managers, banks, and family offices. The platform serves as a central hub for investment decision-making, offering three core solutions: AI-Driven Investment Insights, Portfolio Studio, and StoryFolio. By processing millions of market data points through a proprietary AI engine, Sphere provides forward-looking views on expected risk and return at single-stock, sector, and asset class levels. This allows investment professionals to replace subjective biases with data-driven indicators and market regime analysis. In practice, the platform enables massive scalability for wealth managers through its Portfolio Studio. Users can automate the creation, personalization, and rebalancing of thousands of portfolios simultaneously while strictly adhering to specific investment constraints and tracking error objectives. Beyond technical portfolio management, Sphere addresses the reporting burden with StoryFolio, which utilizes Generative AI to translate complex financial data into tailored, clear investment narratives. This automated commentary system ensures that client reports are not only accurate but also uniquely relevant to each individual portfolio's performance. Sphere is primarily designed for high-level financial roles, including investment committees, portfolio managers, and client relationship officers within large-scale financial institutions. It is particularly effective for teams looking to digitalize their investment process or those requiring high-volume customization that would be impossible to manage manually. The platform’s integration of ESG criteria and its status as a UN PRI signatory make it a preferred choice for institutions committed to responsible investment frameworks across the UK, Europe, and the US. What sets Sphere apart from general financial software is its "Secure by Design" architecture and scientific heritage. The platform is backed by a team of over 100 physicists, data scientists, and engineers, focusing on a scientific method approach to finance. It is ISO 27001 certified and maintains a strict policy of not training its AI models on user data, providing the level of security and regulatory compliance required by major global financial institutions. This combination of deep analytical AI for market prediction and Generative AI for reporting creates a comprehensive end-to-end workflow for modern investment management.
Pros & Cons
Supports the mass customization of thousands of portfolios simultaneously.
Combines analytical AI for market data with Generative AI for automated reporting.
Features high security standards with ISO 27001 certification and no training on user data.
Provides unbiased, forward-looking insights based on millions of market data points.
Managed by a large expert team of over 100 physicists and data scientists.
The platform requires a scheduled demo to access features and pricing.
Exclusively targeted at institutional investors rather than individual retail traders.
Does not offer a self-service or free-tier version of the software.
Requires high-level financial expertise to fully leverage the technical insights provided.
Use Cases
Wealth managers can use Portfolio Studio to automate the rebalancing of thousands of individual client accounts while meeting specific constraints.
Asset management teams can utilize StoryFolio to generate automated, tailored investment commentaries for their monthly or quarterly reporting cycles.
Investment committees can leverage AI-driven market regime analysis to gain unbiased insights into macro contexts and asset class positioning.
Institutional investors can integrate Sphere’s AI insights into their existing decision-making processes to enhance speed and scale.
Banks and insurance companies can maintain regulatory compliance using the platform's ISO 27001 certified security and ESG integration.
Platform
Features
• encrypted data storage
• iso 27001 certification
• esg criteria integration
• forward-looking risk and return views
• market regime analysis
• generative ai investment commentaries
• mass portfolio rebalancing
• ai-driven positioning indicators
FAQs
What are the primary components of the Sphere platform?
Sphere consists of three main solutions: AI-Driven Investment Insights for market analysis, Portfolio Studio for automated rebalancing at scale, and StoryFolio for Generative AI-powered reporting.
How does StoryFolio assist with client reporting?
StoryFolio uses Generative AI to automatically produce portfolio-specific commentaries. It translates complex market data into clear, tailored investment narratives that can be shared directly with clients.
Is the data processed by Sphere secure and private?
Yes, Sphere is ISO 27001 certified and employs encryption both in transit and at rest. Importantly, the company maintains a policy of not training its AI models on user-specific data.
Can Sphere handle a large number of customized portfolios?
Yes, the Portfolio Studio is specifically designed for mass customization, allowing managers to rebalance thousands of unique portfolios while maintaining controlled tracking errors.
Does the platform support ESG-focused investment strategies?
MDOTM, the creator of Sphere, is a signatory of the UN PRI and integrates ESG criteria into its AI-driven investment processes to support responsible investing.
Pricing Plans
Custom / Demo
Unknown Price• AI-Driven Investment Insights
• Portfolio Studio rebalancing
• StoryFolio Generative AI reporting
• Market regime analysis
• ESG criteria integration
• ISO 27001 security standards
• Mass portfolio customization
• Forward-looking risk indicators
• Dedicated AI expert support
Job Opportunities
Senior Backend Developer
Personalize and scale portfolio rebalancing while automating investment commentaries with this AI platform built for institutional asset and wealth managers.
Benefits:
Competitive salary & truly flexible work environment
Unlimited learning & development budget
Collaborate daily with an ultra-international team
Annual company retreat at a stunning location
Fast-track career progression
Experience Requirements:
Strong experience in Java & Spring Boot (microservices, REST APIs)
Proficiency with SQL & NoSQL databases
Experience with software architecture patterns (Layered Architecture, DDD, Event-Driven Design)
Experience with TDD and testing best practices (JUnit, Mockito, Testcontainers)
Experience with messaging systems (ActiveMQ, Kafka)
Other Requirements:
Good knowledge of English (both written and spoken)
Excellent communication skills
Responsibilities:
Develop, maintain, and optimize scalable Spring Boot applications
Implement clean, modular, and testable Java code
Design and optimize relational (MySQL) and NoSQL (MongoDB) databases
Implement and follow best practices in software architecture
Troubleshoot and optimize backend performance and security
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Junior Frontend Developer
Personalize and scale portfolio rebalancing while automating investment commentaries with this AI platform built for institutional asset and wealth managers.
Benefits:
Flexible smart working policies
Annual retreat for the team in an awesome location
Professional development under the lead of a senior member
Free coffee and snacks
Office kitchen and common spaces
Experience Requirements:
1+ years experience working as frontend developer
Coding experience with TypeScript
Knowledge of REST API
Experience with GIT and software versioning
Other Requirements:
Outstanding communication skills
Fluent in English both spoken and written
Responsibilities:
Develop interfaces using TypeScript and React
Lead the adoption of frontend best-practices within the company
Collaborate with technical team members and business partners
Research and develop novel solutions and as part of a team
Produce robust, reliable, scalable high quality solutions
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Data Analyst
Personalize and scale portfolio rebalancing while automating investment commentaries with this AI platform built for institutional asset and wealth managers.
Benefits:
Flexible smart working policies
Annual retreat for the team in an awesome location
Professional development under the lead of a senior member
Free coffee and snacks
Office kitchen and common spaces
Education Requirements:
Master’s degree or PhD in Engineering, Computer Science, Statistics, Physics, Mathematics, or related technical fields
Experience Requirements:
1+ years of work experience in a industry, university, or government lab
Strong skills in statistical modeling and machine learning
Relevant coding experience in programming languages such as Python
Other Requirements:
Excellent teamwork skills are a must
Creativity and ability to formulate problems and solve them
Willing to work towards long-term ambitious research goals
Fluent in English both spoken and written
Responsibilities:
Work on data analytics projects using internal tools and Python
Research and deliver insights related to risk exposures and quantitative analysis
Evaluating and interpreting the outputs of the models
Producing clear written summaries of research results
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Ratings & Reviews
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