Alibaba Cloud Releases Qovest, an AI Investment Research Workbench

On November 2, Alibaba Cloud officially released Qovest, an AI investment research workbench for professional institutional investors. Users submit a research request in a single sentence, and Qovest automatically queries data, collects materials, performs in-depth analysis, generates a report, and continuously tracks the research subject at a set frequency. Unlike one-off Q&A, Qovest can archive each research result in a research space, allowing a research project to be carried forward without starting from scratch every time. Qovest will soon launch an enterprise edition to serve the investment research teams of financial institutions and enterprises.

Professional investors demand far more from agents than everyday chat: data must be real-time and accurate, outputs must have clear sources, and research conclusions must be professional and reliable. To this end, the Qovest team purchased authoritative financial databases, deployed them on Alibaba Cloud, and developed its own agent engineering framework (Harness) for financial scenarios, connecting the entire workflow from data retrieval to analysis output so that delivered results are more accurate and professional. In internal head-to-head evaluations on the open-source financial benchmarks FinFirst and IRAB, Qovest led mainstream products in the evaluation in answer quality, response speed, and cost.

"We want to hand the time-consuming, highly repetitive work in the investment research process to AI, and give time back to the places that truly require professional judgment," said the head of product for Qovest.

The Qovest homepage provides multiple investment research case templates. Users can select their own targets as research subjects, set scheduled tasks, connect their own trading notes, and obtain visualized in-depth research results. For example, users can ask Qovest to break down the per-unit value and domestic content level of each segment in the humanoid robot industry chain, producing an interactive industry-chain map; they can also ask Qovest to estimate the investment scale of power facilities for data centers—adjust any one underlying assumption, and Qovest automatically recalculates.

Beyond in-depth research, Qovest can also keep research running along with the market. One fund manager set up a tracking study for a certain "gold ETF" in Qovest: after defining variables such as the international gold price, the dollar index, global ETF holdings, and central bank gold purchases, Qovest automatically updates the data every week, breaks down the respective shares of exchange-rate factors and rate-hike expectations in that week's gold price moves, and generates a dynamic tracking dashboard. From then on, every time the research page for this ETF is opened, Qovest can continue the analysis from where it left off.

This experience of "not starting from scratch every time" comes from Qovest's "research space." Connected with Qovest conversations, it automatically archives research results, personal trading notes, and questions to be verified, making research traceable and comparable. In the future enterprise edition, the "research space" will become a research scheduling center for collaboration and information sharing among members of an organization.

Qovest's official website is currently open for invitation-based testing to individual users. New users receive corresponding credits upon registration for a free trial, and can subsequently choose a monthly subscription plan of 99 yuan or 199 yuan, each including a corresponding usage quota.