Full-Time
Updated on 9/4/2026
AI-powered investment research platform for equities
CA$100k - CA$220k/yr
Toronto, ON, Canada
Remote
Remote within Canada, with occasional in-person work in downtown Toronto.
Bachelor's
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FinChat by Stratosphere Technology Inc. offers an AI-powered investment research platform for global equities. Its FinChat Copilot answers complex financial questions in plain language by analyzing institutional-grade data, including KPIs, earnings transcripts, revenue segments, and analyst estimates for over 100,000 public companies from providers like S&P Market Intelligence. The platform serves both retail investors and professional institutions with tiered subscriptions (including a freemium option) and an API for embedding the AI chat into other trading platforms. The goal is to speed up research, improve decision quality, and broaden access to advanced financial analytics.
Company Size
11-50
Company Stage
Grant
Total Funding
$14.4M
Headquarters
Toronto, Canada
Founded
2021
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Remote Work Options
Unlimited Paid Time Off
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Vision Insurance
Stock Options
Company Equity
Hybrid Work Options
Introducing Employee Data, now live in Fiscal.ai Terminal, MCP & API. Since its founding, Fiscal.ai has been building the modern financial data company, combining a powerful research Terminal with developer-friendly APIs that serve thousands of customers and millions of end-users globally. Today, Fiscal.AI is launching Employee Data, live across the Fiscal.ai Terminal, MCP, and API. It answers a question that sits underneath almost every efficiency and productivity analysis: how many people does a company employ, and how much is each of them generating? What Employee Data does. Employee Data brings company headcount together with the fundamental line items analysts already use, calculated on a per-employee basis. Metrics include: * Total Employee Count * Revenue per Employee * Gross Profit per Employee * EBITDA per Employee * Free Cash Flow per Employee * And more Coverage spans more than 13,000 companies globally, with history reaching back over 20 years and 40 quarters. What makes this so useful is straightforward: workforce efficiency is one of the clearest signals of how well a company is run, and it's historically been one of the hardest metrics to pull cleanly across a large set of companies. "Fiscal.ai's Employee dataset goes beyond the standard financial statements to provide a more granular view of a company's underlying efficiency. Now, through both the Fiscal.ai Terminal, MCP, and API, clients can easily analyze and compare multiple companies simultaneously across a variety of employee-based metrics." - Ryan Henderson, Head of Research, Fiscal.ai Getting started. Employee Data is available now in the Fiscal.ai Terminal, MCP, and API. This launch is another step toward its mission: making institutional-quality financial data as accessible and actionable as possible, wherever and however investors choose to work. Full documentation and information are available at docs.fiscal.ai. Fiscal.ai is the modern financial data company, building the infrastructure that powers the world's leading investors and platforms. Fiscal.AI deliver institutional-grade financial data with click-through auditability, available within minutes after filings, through Terminal, its all-in-one research platform; its Data Feed API, which powers institutions and investing platforms; and its MCP Connector, which brings accurate, source-linked data directly into AI tools. Its mission is to provide 100 million investors with high-quality financial data. Contact Fiscal.AI. A member of its team will reach out shortly.
Google launches Gemini Enterprise for financial services. Thu, 27th Aug 2026 (Today) Google Cloud has introduced Gemini Enterprise for Financial Services, aimed at capital markets and corporate banking. The offering brings Google's Gemini Enterprise platform into financial research and related workflows. It combines reusable, task-specific skills, connections to licensed and internal data sources, managed agents and a partner network for implementation. At the centre of the launch is a Financial Research agent that can run end-to-end research tasks. Google said it includes explainability features such as confidence scores, stated methodologies, data snapshots for audit purposes and source citations. Analysts can use the agent in the Gemini Enterprise app or connect it to existing workflows through Agent-to-Agent APIs. Google Cloud is positioning the product for work that depends on strict controls over data access and traceability. Access to connected systems remains subject to existing entitlements, meaning licensed market data and permissioned internal information stay within current controls. The product also includes a single control dashboard for IT and risk teams. Google said it enforces security policies, preserves private data isolation and requires outputs to be grounded in traceable citations. Financial workflows Google outlined several use cases across banking and investment operations, including credit risk assessment, portfolio monitoring, market news synthesis, Know Your Customer research and investigative financial analysis. The system can process content from PDFs, spreadsheets and regulatory filings to help map corporate ownership structures, assess risk profiles and identify ultimate beneficial owners. Google also pointed to applications in bond portfolio risk analysis, credit market pricing research and bond issuance preparation. According to Google, the Financial Research agent includes more than 50 foundational skills. These are designed to help institutions set repeatable methods for tasks such as report formatting, data extraction and research processes. Alongside Google's own agent, the launch includes third-party agents for specialist tasks. Examples include a D&B Business Verification agent for onboarding and KYC work, FlowX agents for loan pack checks and document reconciliation, an Obin Financial agent for financial analysis and S&P Global agents for multi-step analysis and report generation. Connector network A key part of the launch is a set of secure Model Context Protocol connectors to financial technology and data platforms. Google said the product can connect with tools used for productivity, market data, ratings, private markets research, regulatory records and digital asset information. Named providers include Google Workspace and Microsoft 365 for productivity. Data and research integrations listed by Google include Daloopa, FactSet, Finnhub, Fiscal.ai, Guidepoint, S&P Global, Moody's, MSCI, PitchBook, SEC Edgar, Dun & Bradstreet and CoinDesk Data and Indices. Customers can also work with systems integrators and fintech partners including Accenture, Capgemini, Cognizant, Deloitte, Genpact, Infosys, KPMG, PwC and Slalom to customise deployments and fit the product into their technology environments. Industry input Google said it developed the service alongside financial institutions including Deutsche Bank and CME Group. Deutsche Bank was identified as a design partner for the Financial Research agent. "As a design partner for the Financial Research agent, Deutsche Bank has helped shape this capability in view of the realities of a highly regulated industry - from data protection and governance to the workflows our teams use every day," said Marie-Jeanne Deverdun, Chief Technology, Data and Innovation Officer, and Member of the Deutsche Bank Management Board. "Starting in the Corporate Bank, we see significant potential to reduce manual research effort, improve the consistency and auditability of outputs, and give our teams more time for client conversations. This is an important step in applying AI where it can make a practical difference: safely, responsibly and at scale." The launch adds to Google Cloud's push to tailor generative AI products for regulated industries, where data governance, audit trails and controlled access are often decisive in procurement. Financial institutions have been testing AI tools for research, client reporting, onboarding and risk work, but many have moved cautiously because of concerns about hallucinations, opaque sourcing and restrictions on licensed datasets. Google said customer data, business rules, intellectual property, custom agents and model outputs remain private to each organisation and are not used to train or fine-tune Google's foundation models. Gemini Enterprise for Financial Services is available in preview.
Fiscal.ai launches an MCP connector for Gemini Enterprise for Financial Services. Fiscal.AI is proud to announce that Fiscal.ai is working with Google Cloud as an MCP connector for Gemini Enterprise for Financial Services, giving analysts, portfolio managers, and researchers the ability to query institutional-grade financial data directly within Gemini Enterprise. The integration covers the full breadth of Fiscal.ai's data feed: * Financials & Ratios * Stock Prices * Segments & KPIs * Filings * Investor Relations (Transcripts, Audio, Press Releases, Slides) * Fund Letters * Adjusted metrics * News * Ownership Data And more, brought directly into Gemini Enterprise for Financial Services without switching context or rebuilding data pipelines. The MCP connector enables AI models to seamlessly interact with external data sources and tools using a standardized, open protocol. With this launch, analysts and portfolio managers can now prompt and converse with Fiscal.ai's real-time financial data within Gemini Enterprise for Financial Services. What makes this so powerful is straightforward: AI responses grounded in verified data, with near-zero latency. "We're partnering with Google Cloud as a native connector in Gemini Enterprise for Financial Services. Now investors can power their workflows right in Gemini Enterprise with trusted structured and unstructured data content." - Braden Dennis, CEO, Fiscal.ai Since its founding, Fiscal.ai has been building the modern financial data company, combining a powerful research terminal with developer-friendly APIs that serve hundreds of thousands of customers and millions of end-users. This collaboration with Google Cloud is a meaningful step toward its mission: making institutional-quality financial data as accessible and actionable as possible, wherever and however developers and analysts choose to work. "Working with Fiscal.ai allows us to bring institutional-quality market data directly into Gemini Enterprise. Together, we're removing friction for financial professionals, enabling them to surface actionable insights wherever they choose to work." - Satish Thomas, Vice President, Google Cloud Contact Fiscal.AI. A member of its team will reach out shortly.
Meet the Fiscal.ai team: Lloyd Mabuto, Head of Design. At most companies, design is a layer applied after the decisions are made. At Fiscal.ai, it's built into the foundation and Lloyd Mabuto is the person making that happen. As Head of Design, Lloyd shapes how Fiscal.ai looks, feels, and communicates trust. In financial data, that's everything. When investors and developers rely on your platform to make real decisions, the design isn't decoration, it's a part of the product. Lloyd comes to Fiscal.ai with a background in UI/UX design and product management across government, healthcare, and education. Working across those industries, each with its own high-stakes audiences and constraints, taught him to design for real people in complex environments, and to treat the product and the visuals as a single thing, not two separate aspects. Q: What excites you most about working at Fiscal.ai? Design actually matters at a company built on financial data, because the whole promise is that you can trust what you're looking at. I get to shape how that trust feels, from the first pixels you see down to the product itself. That's rare on its own. What makes it better is the people. Everyone I work with cares about how they shape its product and is easy to communicate with, there's always something fresh going on, and every team has its own wins worth getting excited about. Q: What's your favorite part of Fiscal.ai's data products? My favorite part is seeing the MCP come to life. Working off accurate and reliable data straight from tools like Claude changes how you use it. Instead of searching all over the place for what you need, the data is just there in the work you're already doing. Q: Tell Fiscal.AI about yourself outside of work. Most of my time outside work goes to family and friends. When it's not burning hot out, nature and travel are big ones for me. I love trying foods from different cuisines, and I'm a bit of a coffee person too. In my spare time I'm usually making art, or listening to and making music. Q: What's a story from inside the team that captures what it actually feels like to work here? Recently I worked on the rebrand and the website redesign, and the two happened in tandem. It started as conversations about the feeling Fiscal.AI wanted to get across. Fiscal.AI built a world and tone rooted in the company's pillars first, and the visual system fell into place right after. The best part was how in sync Fiscal.AI were, everyone pulling in the same direction equally. Fiscal.AI went from loose references to a finished, shipped redesign in a matter of weeks. Each phase pushed into the next, and using that momentum to build was the fascinating part for me. Fiscal.ai is a financial research and data platform built for investors, developers, and institutions. Through its research Terminal and modern APIs, Fiscal.ai provides access to high-quality financial data that powers applications, research workflows, and AI systems. The company has raised $13M in venture funding and serves thousands of customers worldwide. Contact Fiscal.AI. A member of its team will reach out shortly.
Nvidia stocks eye beat-and-raise quarter as AI demand stays strong. 2026-08-20 00:57:17 Key takeaways. * Nvidia is scheduled to report fiscal second-quarter 2027 earnings on Aug. 26 with beat-and-raise expectations. * Fiscal.ai projects Nvidia Q2 FY2027 revenue of $91.48 billion, more than double year-earlier $45.55 billion. * Nvidia deployed $18.6 billion into private companies and infrastructure funds during the April quarter. Nvidia (NVDA) stock fell 1% on Wednesday to close at $217.56 and is down 4% this week as the company heads into next week's earnings report scheduled after the closing bell on Aug. 26. Wall Street expects another beat-and-raise quarter, with Fiscal.ai projecting fiscal second-quarter 2027 revenue of $91.48 billion, more than double the $45.55 billion recorded a year earlier, and adjusted earnings per share of $2.07, up from $1. Jefferies called AI demand signals 'rock-solid,' citing stronger cloud revenue at Microsoft and Amazon, SpaceX's upcoming all-Nvidia deployment, and OpenAI's compute commitments through 2030. Analysts maintain confidence in demand for Nvidia's chips as accelerating cloud spending and major AI commitments reinforce the company's market position. Analysts expect beat-and-raise quarter for Nvidia stocks. Jefferies expects a beat-and-raise quarter driven by Nvidia's 'low valuation and new product cycle,' citing stronger cloud revenue at Microsoft and Amazon, SpaceX's upcoming all-Nvidia deployment, and OpenAI's compute commitments through 2030. Stifel reiterated its 'Buy' rating and $282 target, implying a 30% upside, as hyperscaler spending and AI infrastructure orders remain strong. Its supply-chain checks indicate GB300 demand could hold into early 2027 as Vera Rubin ramps. Morningstar's $280 fair value implies a 29% upside, driven by data-center revenue potentially exceeding $300 billion in 2026 and $500 billion in fiscal 2028. TD Cowen warned that earnings may not resolve questions around margins, product timelines, and AI spending, noting that 'earnings that should have been a positive catalyst for the stock haven't been in recent quarters.' Nvidia Q2 FY2027 revenue and earnings projections. Fiscal.ai expects Nvidia to report revenue of $91.48 billion, more than double the $45.55 billion recorded a year earlier. Adjusted earnings are projected to hit $2.07 per share, up from $1, while earnings before interest, taxes, depreciation, and amortization (EBITDA) are expected to climb to $61.83 billion from $27.58 billion. On a sequential basis, Koyfin estimates that revenue will rise nearly 13% to $92.01 billion. Adjusted earnings are forecast to increase 11% to $2.08 per share, while EBITDA is expected to grow 13% to $62.09 billion. Investors will track Nvidia's gross margins as high-bandwidth-memory costs increase, alongside updates on China sales and the Rubin Ultra roadmap. Nvidia enters $500 billion AI financing arrangements. Nvidia recently entered partially backstopped arrangements involving $500 billion with large asset managers to mobilize funding for AI computing infrastructure. Smaller deals with Sharon AI and Firmus point to an emerging strategy in which Nvidia helps finance data-center projects that ultimately buy its hardware. Nvidia is reportedly considering an investment in AI data-labeling startup Mercor at a potential $20 billion valuation. Nvidia paid Mercor tens of millions of dollars last quarter for expert-curated data used in its Nemotron models. The chipmaker deployed $18.6 billion into private companies and infrastructure funds during the quarter ended in April, exceeding its investment total for the entire previous year. Retail sentiment for NVDA stocks turns extremely bearish. On Stocktwits, retail sentiment for NVDA deteriorated further to 'extremely bearish' from 'bearish' levels a day ago amid a 12% rise in 24-hour message volume. One user said, '$NVDA Historically never been up during Earnings. Still holding and hoping for the best.' Another user said, '$QQQ would feel much better about big long bets if $NVDA were in 190s heading into the print. Going to be a double beat but this cheap computer overhang a tough sell over 215.' Nvidia is the best-performing 'Magnificent Seven' stock this year, tied with Apple at a 17% gain. Faq. What did Nvidia stocks do on Wednesday? Nvidia (NVDA) stock fell 1% on Wednesday to close at $217.56 and is down 4% this week. When will Nvidia report Q2 FY2027 earnings? Nvidia will report fiscal second-quarter 2027 results after the closing bell on Aug. 26. What are analysts projecting for Nvidia's Q2 FY2027 revenue? Fiscal.ai projects Nvidia will report revenue of $91.48 billion, more than double the $45.55 billion recorded a year earlier, with adjusted earnings per share of $2.07, up from $1. Disclaimer: The information on this page may come from third-party sources and is for reference only. It does not represent the views or opinions of Gate and does not constitute any financial, investment, or legal advice. Virtual asset trading involves high risk. Please do not rely solely on the information on this page when making decisions. For details, see the Disclaimer.