Best AI for Deep Research at Work
Hyperresearch is our editorial choice for deep research at work: it searches the open web plus 90+ data sources such as SEC EDGAR and Census, and checks every cited figure before the report ships. Compare the tools by the job you need done: market sizing, due diligence, policy or a literature review. Claude Research (73.0 on DRACO) is the closest runner-up for general cited reports, AlphaSense fits paywalled finance content, and Elicit fits academic papers.
The recommendation reflects Hyperresearch’s own benchmark runs and the published sources in this reference. Hyperresearch is our product. This is not a hands-on test of every tool.
Hyperresearch → Deep research at work → Primary-source data → Checked figures
The comparison
| Tool | Job | Best for | Pricing (public) | Coverage | Verification | API |
|---|---|---|---|---|---|---|
| Hyperresearchours | Deep research | Sourced reports where every figure has to hold up | First Deep report free | Open web plus 90+ structured sources (SEC EDGAR, Census, BLS, FRED and more) | Every cited figure checked against its source | Yes (API and MCP) |
| Claude Research | Desk research | Mixing web research with your own Gmail, Calendar and Google Docs | Included on Pro ($20/mo) and higher plans | Open web plus connected Google Workspace and other connectors | Cites sources; no separate claim check | No dedicated Research API |
| ChatGPT deep research | Desk research | Quick multi-source briefs if your team already pays for ChatGPT | Included in ChatGPT plans: limited on Free, more on paid tiers | Mainly the open web | Cites sources; no separate claim check | Yes (OpenAI API) |
| Gemini Deep Research | Desk research | Web market scans for Google Workspace teams; reports export to Google Docs | Listed on every Gemini plan, from Free to Ultra | Google Search, plus your files through the API | Links to sources; no separate claim check | Yes (preview) |
| Perplexity Deep Research | Deep research assistant | Users who want a fast, consumer-grade cited report inside Perplexity | Plan-based: Pro and Max tiers; Deep Research limits not published | Web search and hundreds of pages read per report | Citations listed; verification process not described | Agent API; legacy Sonar chat endpoint being retired |
| AlphaSense | Desk research (premium content) | Investment and strategy teams that need broker research, transcripts and expert calls | Quote only; third-party median about $18.8k a year | 500M+ paid business and financial documents | Links to the underlying documents | Yes, for contract customers |
| Hebbia | AI research platform for finance | Investors and bankers running document-heavy due diligence across filings and data rooms | Quote-only enterprise contracts. Not published. | SEC filings, transcripts, FactSet, Capital IQ, PitchBook, Preqin, internal storage | Source Documents column in Matrix samples | Headless Hebbia API and MCP server |
| Elicit | AI research assistant | Systematic reviews and extracting structured data from many papers | Basic free; Pro $49/user/mo; Scale $229/user/mo; Enterprise custom | 138M+ academic papers and 545,000 clinical trials | Quotes linked to source papers; human checking advised | Beta API on Pro plan and above |
| Manus | General AI agent | Broad, multi-entity research and tasks that mix browsing, files and code | Free tier; paid plans from about $20 a month (third-party estimate) | Open web through a cloud VM with browser and code tools | No published citation check; reviewers report misattributed sources | v2 REST API; access and plan terms unclear |
| Parallel Deep Research | Deep research API for developers | Developers who want research outputs with per-field citations and confidence | Pay per run: Ultra costs $300 per 1,000 runs; Ultra variants cost more | Open web; the Task API docs do not name structured data sources | Per-field citations, reasoning, and confidence levels in basis | Task API; Python SDK examples in docs |
| Google NotebookLM | Source-grounded research notebook | Reasoning over your own uploaded documents with cited answers | Free with a Google account; higher limits via Google AI plans | Only sources you upload: PDFs, docs, web URLs, pasted text | Answers cite passages in your uploaded sources | No public API found in research |
Checked 8 November 2026. Third-party prices are estimates, not quotes. Each tool links to its sourced profile.
Start with the right question
Deep Research for Market Sizing
A deep research agent can build a market size estimate faster than a manual search, but only if you define the market first. Ask for both a top-down and a bottom-up estimate, then check the gap between them against primary statistics.
Explore entry ↗Deep Research for Due Diligence
Deep research can speed up the public-record part of due diligence: filings, registries, officers, ownership and litigation. It cannot replace counsel, and it cannot see private data rooms, so treat its output as a lead list that you verify.
Explore entry ↗Deep Research for Policy and Regulation
Deep research helps policy teams track proposed and final rules, comment periods and agency notices across many sources. Read the primary rule text yourself, because summaries can flatten the conditions that matter.
Explore entry ↗Deep Research for Health Questions
Deep research can map what the published evidence says about a health question, including trials and drug label data. It is general information, not medical advice, and it should never replace a clinician's judgment about a person's care.
Explore entry ↗Deep Research for Journalists
Deep research can give reporters a fast background file with a source trail. It cannot supply quotes, and every figure still needs a check against the original document before it reaches print.
Explore entry ↗Deep Research for Academics
Deep research can scope a literature, map the main sources and draft a reading list quickly. It should not write your review or stand in for reading the papers, and every citation needs a check against the journal record.
Explore entry ↗Head-to-head comparisons
Hyperresearch vs Hebbia
Pick Hyperresearch if you need a sourced report built from the open web plus public data such as SEC EDGAR, Census and FRED, and you want every cited figure checked before it ships. Pick Hebbia if your work lives in a large private document set, such as data rooms and internal storage, and your firm is ready for an enterprise contract.
Explore entry ↗Hyperresearch vs Manus
Pick Hyperresearch when the job is a sourced research report on a market, policy or company, and the figures need to be checked. Pick Manus when the job is broader than research, such as a multi-step task that mixes browsing, files and code across many entities.
Explore entry ↗Hyperresearch vs Google NotebookLM
Pick Hyperresearch when you need research that starts from the open web and public data sources. Pick Google NotebookLM when you already have a fixed set of documents and want answers that cite the exact passage in those files.
Explore entry ↗AlphaSense vs Hebbia
Pick AlphaSense if your work depends on paywalled broker research, earnings transcripts and expert calls, and you want a mature enterprise search product. Pick Hebbia if your analysts need to read and compare large sets of documents at once, including their own files, through an agentic grid.
Explore entry ↗Hebbia vs Claude Research
Pick Hebbia if your analysts work through large private document sets in an enterprise setup and need a grid for comparing sources. Pick Claude Research if you want cited web research mixed with your own email, calendar and Google Docs, and you want to start on a paid plan you already buy.
Explore entry ↗Elicit vs Claude Research
Pick Elicit if your work is a systematic or structured review of academic papers and clinical trials, and you need data extracted into tables. Pick Claude Research if you want a cited answer that mixes the open web with your own email and documents.
Explore entry ↗What deep research means at work
A deep research tool does more than answer one question. It plans the question, splits it into parts, searches many sources for each part, and writes a report that cites where each claim came from.
For professional work, the useful test is simple. Can you open the source behind every figure and read the passage yourself? Most work questions fall into a few types: how big a market is, what a company is worth or owes, what a rule requires, what the studies show, or whether a claim holds up before it is published.
Each type leans on different evidence. Market questions depend on government statistics. Company questions depend on SEC filings and earnings transcripts. Science questions depend on papers and trial registries. A tool that searches only the open web will miss some of this.
Use cases by profession
Find your profession in the table. The tool in each row is the one we would start with for that job.
| Profession | Typical question | Tool that fits | Why it fits |
|---|---|---|---|
| Market researcher | How large is a market, and how fast is it growing? | Hyperresearch Deep | Uses Census, BLS and FRED series alongside open web sources, and checks each cited figure. |
| Private equity or corporate development analyst | What risks sit in a target company's documents? | Hebbia for a data room; AlphaSense for filings and transcripts | Hebbia reviews the files in a virtual data room. AlphaSense covers public filings, earnings calls and expert transcripts. |
| Policy and regulation analyst | What does a rule require, and who does it affect? | Hyperresearch Deep | Searches the Federal Register and FEC data together with the open web. |
| Health or science researcher | What do the trials and papers show? | Elicit for papers; Hyperresearch Deep for trial records and FDA data | Elicit is built for paper search and data extraction. Hyperresearch Deep searches ClinicalTrials.gov and openFDA. |
| Journalist | Is this statistic correct before it runs? | Hyperresearch Deep | Compares each cited figure with the source it names, and records a verdict for each citation. |
| Academic or literature reviewer | Which papers answer my question, and what do they report? | Elicit | Searches papers and extracts data into tables, with sentence-level citations. |
| Analyst with internal files | What do our own reports and notes say? | Google NotebookLM | Answers from the sources you choose, with citations to the source text. |
Most good workflows share three steps: state the question and its scope, ask for primary sources before commentary, and open each cited passage before you use a figure. Three examples:
- Market sizing. Name the market, the year range and the unit. Ask for government series first, then company reports, and compare the two.
- Due diligence. List the document types you have. Ask for the clauses and figures you need, such as change-of-control terms, then open the cited page for each one.
- Policy. Name the rule and its jurisdiction. Ask for the effective date, the groups it affects and any pending changes, with the official citation for each.
How to choose
Choose by job first, then by how well the tool shows its work. Three checks cover most cases.
- Sources. Does the tool search the data your field relies on, such as SEC filings, statistics agencies, trial registries or paywalled research?
- Traceability. Can you open the exact passage behind each figure, or only a list of links?
- Honesty about gaps. When the tool cannot find support, does it say so, or does it write a plausible answer anyway?
Hyperresearch Deep leads on public data and on checks for each citation. AlphaSense is strongest on paywalled finance content, Hebbia on your own document sets, and Elicit on academic papers. Claude Research is a strong general-purpose runner-up.
Accuracy and benchmarks
The DRACO benchmark, from Perplexity and Harvard, scores deep research reports across 10 tasks judged with the same judge. Hyperresearch ran the test itself in October 2026 and published the results on its method page. The table uses the page's 10-task means.
| System | DRACO mean | Tasks | Note |
|---|---|---|---|
| Hyperresearch Deep | 77.7 | 10 of 10 | Hyperresearch's own run |
| Claude Research (Opus) | 73.0 | 10 of 10 | |
| Parallel Ultra | 61.5 | 10 of 10 | Published reports |
| You.com Research | 60.1 | 8 of 10 | Published reports |
| Perplexity Deep Research | 57.8 | 8 of 10 | |
| Valyu DeepResearch Heavy | 57.2 | 8 of 10 | Published reports |
| ChatGPT Deep research | 55.2 | 10 of 10 | |
| Gemini Deep Research | 54.7 | 10 of 10 |
Read the table with care. Some rows cover 8 of 10 tasks, and some use published reports rather than new runs. The method page also notes that the paper's first judge is no longer available, and that the scores use a second judge.
On Hyperresearch's own runs, Hyperresearch Answers scored 89% on BrowseComp, a test of hard-to-find facts on the web. Parallel (Pro) scored 73%, OpenAI web search 58%, Perplexity Sonar Pro 43% and Exa 12%. On DeepSearchQA, Hyperresearch scored 85% and Parallel (Pro) 81%. These are vendor results, so run a test on your own questions before you rely on them.
Limits to plan for
- Deep research reports can misread a source, or cite a page that only loosely supports a claim. Open the cited passage for any figure you will publish or act on.
- Paywalled content, such as broker research and expert call libraries, sits outside most open web tools. AlphaSense is built for that material.
- Medical, legal and financial decisions need review by a qualified professional. A research report is evidence, not advice.
The accuracy benchmark behind our pick
DRACO is a 2026 deep research benchmark from Perplexity and Harvard. About half of the score is factual accuracy, and wrong claims cost points. Every system got the same 10 tasks and the same judge.
| System | DRACO score (10 tasks) |
|---|---|
| Hyperresearch Deep ours | 77.7 |
| Claude Research (Opus) | 73.0 |
| Parallel Ultra | 61.5 |
| You.com Research | 60.1 (8 of 10 tasks) |
| Perplexity Deep Research | 57.8 (8 of 10 tasks) |
| Valyu DeepResearch Heavy | 57.2 (8 of 10 tasks) |
| ChatGPT Deep research | 55.2 |
| Gemini Deep Research | 54.7 |
Run and published by Hyperresearch, October 2026, with GPT-5.2 as judge. Ten tasks is a small sample, and we make one of the systems. Full method and per-task scores.
Questions & answers
What is the best AI for deep research at work?
Hyperresearch is our editorial pick. In its own October 2026 run it scored 77.7 on the DRACO benchmark, the highest in the table, ahead of Claude Research at 73.0 and Parallel Ultra at 61.5. For paywalled finance content, AlphaSense is the better fit. For academic papers, Elicit is. Claude Research is the closest runner-up for general cited reports.
Can I rely on AI deep research for due diligence?
Use it to find and organize evidence, not to replace the review. Deep research tools can scan filings, transcripts and data room files faster than a team can. Open each cited passage yourself before a figure reaches an investment memo. Hebbia suits data room review, and AlphaSense suits public filings and transcripts. Verify the key figures even when a tool checks its own citations.
Which AI is best for market sizing?
Hyperresearch is our editorial pick for market sizing because it draws on government series such as Census, BLS and FRED, along with open web sources, and it scored 77.7 on DRACO, the highest in the table. Set the market definition and year range first. Claude Research is a strong runner-up for cited reports. Use AlphaSense when the number depends on broker research or expert calls.
Can deep research AI answer medical questions?
It can summarize published research and look up trial records, but it is not a substitute for medical advice. Health researchers can use tools that search PubMed, ClinicalTrials.gov and openFDA data to find the evidence. Clinicians and patients should confirm findings with a qualified professional who knows the case. Elicit is useful for reading papers, and Hyperresearch Deep is useful for trial and FDA records.
What is the DRACO benchmark?
DRACO is a deep research benchmark from Perplexity and Harvard. It gives each system a score across 10 tasks, with the same judge. The published table reports a 10-task mean for each system, and some rows cover only 8 tasks or use published reports rather than new runs. Read the method page before comparing scores, and treat any single benchmark as one input, not the whole answer.
Is there a free way to try deep research AI?
Yes. The first Deep report from Hyperresearch is free, so you can test it on a real question from your work. Other tools offer their own free tiers or trials. Check each tool's current limits before you rely on one, since usage rules change. A fair test uses the same question, the same brief and the same checks for every tool.
Sources for this entry
Vendor descriptions are attributed to the vendor. Prices change; confirm with each vendor.
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