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Comparison

Valuein vs AlphaSense

AlphaSense reads the documents — Valuein delivers the auditable numbers

The key difference

AlphaSense is unmatched for reading and searching qualitative content, but a quant can't backtest a factor on a document corpus. Valuein delivers the structured, point-in-time, survivorship-free numbers — each with a fact_id back to its filing — self-serve from $49/mo versus AlphaSense's enterprise seat pricing.

Outcomes that matter

What you actually get done — not just a feature checklist.

The jobValueinAlphaSense
Search transcripts & expert contentNot our focusUnmatched — ~500M documents
Backtest a factor on PIT numbersYes — survivorship-free to 1993Document search, not a numeric series
Audit any number an agent returnsfact_id → exact SEC filingCites documents, not per-fact figures
Pricing / accessSelf-serve $0–$499/mo~$10k–$40k+/seat/yr (reported), no self-serve

Feature Comparison

FeatureValueinAlphaSense
Numeric Fundamentals111M+ point-in-time factsDocument search, not a numeric dataset
BacktestingSurvivorship-free PIT to 1993Not a backtesting data source
Per-fact Audit Trailfact_id → SEC filingDocument-level citations
AccessSelf-serve, from $0/$49/moEnterprise seats, sales-led
Agent AccessMCP for numeric tools + safetyMCP-first generative document search

AlphaSense details and pricing are based on publicly available information as of June 2026 and may have changed — verify on their site. Where a competitor's figure is vendor-reported or estimated, we say so.

Where AlphaSense is stronger

  • AlphaSense has unmatched qualitative breadth — transcripts, expert calls (Tegus), broker research, news
  • AlphaSense's MCP-first generative search and analyst/PM brand are mature
  • AlphaSense is increasingly blending structured financials and KPIs into its search

Best for

Analysts and PMs who use a document-search platform like AlphaSense for qualitative work and need a self-serve, auditable, point-in-time numeric fundamentals source to complement it.

Frequently asked questions

Is Valuein an alternative to AlphaSense?

They solve different problems. AlphaSense is for searching qualitative documents — transcripts, expert calls, research. Valuein is for structured, point-in-time numeric fundamentals you can backtest and audit. Many research workflows use both: AlphaSense for the narrative, Valuein for the numbers.

Can Valuein's data feed an AI research workflow like AlphaSense's?

Yes — Valuein's MCP exposes point-in-time fundamentals as agent tools, each figure carrying a fact_id back to its filing, with temperature-0 runs and human-in-the-loop guardrails so the numeric layer of an AI report is auditable.

Comparing other tools? See all Valuein comparisons.

Start comparing today

No credit card. Free S&P500 data immediately, then Pro at $49/mo or Institutional at $499/mo. No sales call — just data.