Manus: a general agent with parallel Wide Research for lead lists

What it is

Manus is a general-purpose AI agent. Its docs describe Wide Research: for jobs with many similar items, such as researching 50 companies, Manus splits the work into sub-tasks and gives each to its own agent with a fresh context, then assembles the results into a table or report. Manus lists “Lead Generation: research 200 prospects, find contact info, qualify leads” among its use cases, and says it has tested up to 250 items.

Ownership. Meta announced it was buying Manus in December 2025. CNBC reports Chinese regulators ordered the deal unwound in April 2026, and Manus says it formally resumed independent operations in August 2026. Some users had to back up and restore their data during the separation.

Best sales uses

• A first-pass account list. Give it 50 or 100 target companies and the columns you want (size, what they sell, a recent change, a source link), and review the table.
• Fit scoring. Give it your criteria and ask it to rate each company and show the evidence.
• Competitor profiles for a battlecard draft.

Who it’s for

SDRs and AEs who start from a list of companies, and owners who sell and need a market scan. Manus’s own docs say Wide Research is not ideal for a single deep analysis, tasks with fewer than 10 items, or tasks where each step depends on the last.

Setup effort

Easy. Sign up, describe the table you want, and say how many items. Manus’s tips: name the columns, state the scale up front, and give your evaluation criteria.

Pricing (checked 2026-10-15)

• Free: $0, 300 refresh credits a day, Chat Mode and Manus 2.0 Lite in Agent Mode, 1 concurrent task.
• Pro: from $20 a month with 4,000 credits, or $40 a month with 8,000 credits. Pro adds Manus 2.0 and 2.0 Max, Wide Research, 20 concurrent tasks, and 20 scheduled automations.
• Team: from $20 per seat a month, with SSO, a data-training opt-out, and usage analytics.
• Annual billing is 17% less. Manus says what the pricing page shows is what counts.

Caveats

• People’s data. Finding contact information for individuals raises consent and privacy rules, and some sites forbid scraping. Read Safe Use first and use public business information.
• Check the table. A 200-row table with a wrong row in it is still wrong. Spot-check rows against the source.
• Don’t scrape LinkedIn. LinkedIn’s terms ban scraping and unapproved automation, per our Safe Use page.
• Credits. Large parallel jobs use credits quickly. Start with 10 rows.