Boosted.ai vs QuantumStreet AI (2026)
The decision is whether you want AI to design the portfolio or to brief the people who do. QuantumStreet AI builds the investable product. Its deep learning models weigh hundreds of signals across about 50,000 securities to design indexes and portfolios that banks and asset managers license and launch, more than $8 billion of them by its own count, and its QuantumEdge platform lays forecasts with confidence scores over a client's own research. Boosted.ai builds the analyst. Its Alfa agents watch companies, portfolios and market events and write sourced briefs and memos, with bull and bear agents arguing a name against a fund's own criteria in the institutional tier and a white label version for brokerages. The two publish almost opposite things. QuantumStreet AI names its model platform, IBM watsonx, and publishes no security certification. Boosted.ai holds SOC 2 Type II and ISO 27001, 27701 and 42001, and names no model provider.
- You want research, not a product to license. Boosted.ai's Alfa monitors your coverage and portfolios continuously, investigates material changes and writes cited briefs and memos, leaving the investment decision with your team.
- Your security review starts with certificates. Boosted.ai holds SOC 2 Type II and ISO 27001 and 27701, plus ISO 42001 for its AI management system, with a trust center on Vanta.
- Your data cannot train a vendor's models. Boosted.ai states that client data never trains the underlying models and is never shared across customers, and its privacy policy ties retention to the contract or a deletion request.
- You run a brokerage or build on APIs. Alfa Powered embeds research and portfolio monitoring in your app under your brand, and the Alfa Platform offers a financial event bus and APIs ready for the Model Context Protocol.
- You want an investable strategy. QuantumStreet AI designs indexes and portfolios that clients license and launch products on, including thematic baskets and, since March 2026, a long short global equity strategy.
- You want to test before you launch. Clients can backtest a tailored index before it goes live, and the published index rules are fixed once it does, which makes every result checkable against the methodology.
- You want forecasts with a stated confidence. QuantumEdge delivers one and three month forecasts and signals, each with a confidence score and a plain language explanation, and scores every data source for trust.
- You want to know which AI platform sits underneath. QuantumStreet AI runs on IBM watsonx as an IBM partner, having moved there from Watson Discovery and Watson Studio.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Boosted.ai and QuantumStreet AI are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI FinTech Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Boosted.ai | QuantumStreet AI | |
|---|---|---|
| Primary category | Capital Markets & Research AI | Capital Markets & Research AI |
| Founded | 2017 | 2015 |
| Headquarters | Toronto, Ontario, Canada | San Francisco, California, United States |
| Website | boosted.ai | quantumstreetai.com |
Side by Side
| Axis | B Boosted.ai |
Q QuantumStreet AI |
|---|---|---|
| AI Centrality | ||
| Autonomy and Oversight Model | ||
| Model Risk Management and Transparency | ||
| Operational and Outcome Evidence | ||
| AI Safety and Data Stewardship | ||
| GLBA and Data Privacy Posture | ||
| Security Certifications and Trust Center | ||
| Regulatory Status and Licensure | ||
| AI Governance and Bias Disclosure | ||
| AI Liability and Recourse | ||
| Model Supply Chain Disclosure | ||
| Core Systems and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Commercial Transparency | ||
| Institution and Segment Coverage |
The short version of each
Boosted.ai
Boosted.ai builds Alfa, an agentic AI research system that monitors companies, portfolios and market events around the clock and writes briefs and investment memos with every conclusion cited to the filing, transcript or dataset behind it. Alfa Prime gives institutional teams agents that argue bull and bear cases against a fund's own criteria and return a memo with a conviction score, Alfa Powered lets brokerages embed the research under their own brand, and the Alfa Platform offers developers APIs ready for the Model Context Protocol. According to the AI FinTech Index, it holds SOC 2 Type II and ISO 27001, 27701 and 42001, and states that client data never trains the underlying models and is never shared across customers. It names no client institution, no foundation model and no price for any tier. It is based in Toronto and states $5 trillion in client assets supported.
Source: AI FinTech Index, 2026
QuantumStreet AI
QuantumStreet AI designs AI driven indexes and portfolios that asset allocators, investment managers and banks license and build products on, and sells the forecasts behind them through its QuantumEdge platform, APIs and SDKs. Deep learning models weighing hundreds of signals across about 50,000 securities generate the methodologies, and each one and three month forecast carries a confidence score. According to the AI FinTech Index, it runs on IBM watsonx as an IBM partner and states more than $8 billion in client designed indexes and portfolios. A July 2026 release states that 98 percent of its index strategy assets beat their benchmarks in the first half of 2026, without naming the benchmarks. It publishes no security certification, names no client institution and does not mention on its own site that IBM describes it as the institutional division of EquBot.
Source: AI FinTech Index, 2026
Common questions
Is Boosted.ai or QuantumStreet AI better for institutional investors?
They do different jobs. QuantumStreet AI designs indexes and portfolios that banks and asset managers license and build products on, and sells the forecasts behind them. Boosted.ai's Alfa is a research system that monitors names and portfolios and writes cited briefs and memos for an investment team that keeps the decision. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
How do Boosted.ai and QuantumStreet AI show their AI is right?
QuantumStreet AI attaches a confidence score to each forecast, lets clients backtest an index before launch and states that 98 percent of its index strategy assets beat their benchmarks in the first half of 2026, weighted by assets and without naming the benchmarks. Boosted.ai cites the source behind every conclusion and adds a conviction score in its institutional tier, and publishes no accuracy figure for monitoring or extraction. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Which AI models do Boosted.ai and QuantumStreet AI use?
QuantumStreet AI runs on IBM watsonx as an IBM partner, having used Watson Discovery and Watson Studio before that. Boosted.ai describes multi model agents and names no foundation model or model provider. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Will Boosted.ai and QuantumStreet AI pass an institution's vendor review?
Boosted.ai holds SOC 2 Type II and ISO 27001, 27701 and 42001, with a trust center on Vanta, and stores most data in Canada and the US on Amazon Web Services. QuantumStreet AI publishes no attestation, certification or trust center, and IBM's infrastructure assurance belongs to IBM rather than to QuantumStreet. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Can a brokerage or developer build on Boosted.ai or QuantumStreet AI?
Boosted.ai sells to both: Alfa Powered embeds research under a brokerage's own brand, and the Alfa Platform offers APIs ready for the Model Context Protocol. QuantumStreet AI delivers forecasts through APIs and SDKs behind an access request, with documentation kept private. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Where does each publish the most, and the least?
Boosted.ai publishes most on its security certifications, its data handling and how its research cites sources, and says little about pricing, accuracy testing, the models it is built on or its clients. QuantumStreet AI publishes most on how its models build strategies and score forecasts, and says little about pricing, security certifications, its legal entity or its clients. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified October 7, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Wealth & Advisory AI page.
Neither publishes a price, and neither names a client institution. QuantumStreet AI's performance claim is weighted by assets and names no benchmark, and Boosted.ai publishes no accuracy figure or error analysis for what Alfa monitors and extracts, so neither offers a measured record a client can check line by line. Neither names its market and news data suppliers, beyond sample citations to Bloomberg and Reuters at Boosted.ai. The gaps then split.
QuantumStreet AI names its model platform but publishes no security certification, does not say which entity signs an index license, and leaves its relationship to EquBot, recorded only in IBM's case study, unaddressed on its own site. Boosted.ai carries four named certifications and a categorical commitment that client data never trains the models, but names none of the foundation models its agents use or the retention terms for what reaches them.