AlphaSense vs Rogo vs Altys: Which Research Workflow Fits Your Team?
Compare AlphaSense, Rogo and Altys by sources, research workflows and India coverage. Test evidence, exports and continuity instead of relying on feature counts.
AlphaSense, Rogo and Altys should be compared against the research assignment, not ranked as three versions of the same chatbot. Their public starting points are broad market intelligence, financial workflows and India-first research respectively, with meaningful overlap around evidence and firm context.
For an Indian investment team, or a global desk covering India, the useful question is what remains difficult after the existing data and research subscriptions have done their part.
Updated 15 October 2026. Altys publishes this comparison and is included in it. Descriptions below are based on current public vendor materials, not an independent hands-on benchmark. This update removes older shortcuts about product boundaries; it does not establish that any platform lacks an untested feature.
What the vendors currently describe
AlphaSense’s public platform combines premium external content and internal knowledge with AI research, monitoring and financial deliverables. Its hedge-fund material also describes earnings analysis and company research. It should not be reduced to document search alone.
Rogo’s platform overview describes finance-specific workflows, firm knowledge, source citations and governance. That is broader than an assumption that it only creates banking presentations. Its proposed deployment should be evaluated on the research task the buyer needs.
Altys’s public solutions describe India-first evidence connected to research, scorecards, monitoring and outputs a team can inspect. That local scope is the relevant starting point, not a claim of universal global coverage.
These are different entry points into a research process, not fixed walls around the products. Capabilities, access and entitlements can vary by contract and configuration.
Match the source universe to the assignment
Begin with the actual coverage list, historical periods and document types. “Global coverage” does not tell a buyer whether a particular local segment disclosure is available. “India-first” does not prove that every company and every historical KPI is complete.
Include a difficult disclosure in the test pack: a segment recast, a changed definition or a period that appears in more than one currency. Ask for the original source and the basis used in the answer.
For paid content, distinguish the platform subscription from the content entitlement. A connector does not automatically grant the right to access, export or redistribute every connected dataset. Confirm those rights with the provider.
The India workflow guide for US research desks explains the local units, fiscal periods and reporting-basis checks.
Test the handoff rather than the first answer
A generated memo is an intermediate output. The next step may be a model change, a review meeting or an updated research question. Ask what evidence and assumptions survive that transition.
Give another analyst the resulting work. Can they identify the reporting period, explain a manual adjustment and retrieve the previous view? Can they distinguish an accepted assumption from an unreviewed suggestion?
This is not a feature we assume any candidate has or lacks. It is a test that reveals whether the proposed workflow suits the firm’s review process. Our research-management guide develops the exercise.
Separate citations from calculation verification
A citation can be real and still support a different statement from the one made. Check the entity, period, currency and scope at the cited passage.
A calculation has additional requirements. Its inputs need compatible definitions and the formula needs to be inspectable. An Excel download may contain working formulas, frozen values or both. Open it and identify which is which before treating it as reproducible.
Altys’s public methodology sets out its source, date, comparability and missing-data principles. Use those principles as questions in a demonstration, not as permission to skip verification.
If a value is unavailable, ask whether the system preserves that state or quietly supplies a plausible substitute. A complete-looking table is not necessarily a complete evidence record.
Test context without assuming exclusivity
Firm context matters when two analysts use the same public source but ask different questions. A prior memo, an adopted modelling assumption or an unresolved disagreement can change what the next assignment should investigate.
Both the external source and the private context need clear identities. A private estimate must not become a reported company fact. A current view must not erase the earlier record.
Current vendor materials already discuss aspects of context and memory. The buyer’s job is to test how those ideas work in the actual deployment, including access, versioning and permitted exports. A marketing label alone does not establish research continuity.
Compare the operating burden
A credible evaluation includes the work needed after the demonstration. Which sources require separate licences? Who maintains company mappings? How are failed tasks, revised disclosures and changed definitions handled?
Ask about deployment, privacy, retention and support using the firm’s requirements. Do not infer security certification or regulatory suitability from a research feature. Those questions need their own documented review.
Then compare the total assignment: preparation, analyst checking, correction and reuse. The shortest generated answer is not automatically the least expensive workflow to maintain.
Where the choice becomes clear
If the missing input is a premium content source, investigate that source and its entitlement first. If the bottleneck is an institutional financial assignment, test the end-to-end output and handoff. If the work is Indian company research, put local evidence, dates and comparability at the centre of the evaluation.
A firm can have more than one of these needs. Combining a broad intelligence platform with a specialised local research process can be more sensible than assuming one product must replace the whole stack.
For Koyfin, Pascal AI Labs, Hudson Labs and Bipsync alongside these tools, use the hedge-fund research tools guide. For the narrower Rogo question, use Rogo and Indian equity research.
To discuss Altys, request access with one defined India-focused assignment. The useful outcome is a verified fit for that task, not a claim that a brand wins every category.
Educational software comparison only. No securities recommendations or compliance certification. Altys Labs is not a SEBI-registered Research Analyst or Investment Adviser.
Frequently asked questions
What is the main difference between AlphaSense, Rogo and Altys?
Their starting points differ: AlphaSense emphasises a broad content and market-intelligence universe, Rogo finance workflows and firm context, and Altys India-first research processes. All have broader propositions than a basic chatbot, and overlap should be tested.
Do Rogo and AlphaSense also support research context and monitoring?
Their current public materials describe capabilities beyond one-off answers, including firm knowledge or monitoring workflows. Do not assume these features are exclusive to another product; test the proposed configuration and data entitlements.
Can a US-based team consider Altys?
A US-based team researching Indian equities can request a scope discussion. Altys's public data coverage is India-first; this does not imply a US stock database, execution service or universal replacement for existing subscriptions.
Do citations eliminate financial AI errors?
No. Check whether the cited source supports the exact claim and matches the entity, period, currency and reporting basis. Review calculations independently and test how the system handles unavailable evidence.