Distilla vs AlphaSense: An AlphaSense Alternative for AI Agents?

The short answer

AlphaSense is a terminal-style research platform for fund analysts, built for reading and searching by hand. Its strengths are expert-call transcripts (through Tegus) and full broker research reports, for customers with the entitlement. It is sold through a sales team, and seats typically cost tens of thousands of dollars a year. Distilla is AI-native: an MCP server and HTTP API designed for agentic analysis in Claude, ChatGPT and your own agents. It brings institutional rigor at a much lower entry price, with narrative, structured qualitative and quantitative data in one layer for liquid stocks in the US and Asia.

•           Choose Distilla if your analysis runs through an AI agent, and you want quantitative, qualitative and narrative data in one connection, for liquid US and Asian stocks, without a sales call.

•           Choose AlphaSense if your process depends on expert-call transcripts or full research reports your firm is entitled to, or you need private companies and global coverage inside a platform your analysts read by hand.

•           Use both if you want deep document research in the browser and a data layer for your agents.

Why the comparison matters: agents need data, and data comes in two tiers

An AI agent that analyzes stocks from web search alone can be biased, outdated, incomplete or wrong, and can give different answers on different runs because sources conflict. For anyone using an agent to inform investment decisions, the fix is a data layer behind it, and that layer is worth paying for.

Two kinds of data MCP servers exist today. The enterprise tier (Capital IQ, FactSet, AlphaSense) is sold to funds, priced at the firm level and arranged through sales. A newer self-serve tier (FMP, Finnhub, Financial Datasets, Massive, Alpha Vantage, Distilla and others) is built for individual investors, small teams and analysts, with free tiers, trials or monthly plans.

Financial data also falls into four layers: market data, financials and KPIs, qualitative and narrative data, and company knowledge. AlphaSense is strongest in documents: filings, research and expert calls. Distilla covers more of the layers an agent needs together: structured numbers, structured qualitative datapoints, narrative sources including podcasts, and company knowledge such as drivers and price attribution.

Distilla itself has both tiers. The same data powers an enterprise product, including an agent, used by funds, and it is packaged as a self-serve product so individuals and small teams work from the same facts. This comparison looks at Distilla’s self-serve product against AlphaSense.

Two product shapes

AlphaSense is built for analysts at a terminal. It describes itself as an AI-powered market intelligence platform. Analysts search, read and set alerts inside AlphaSense, with mobile apps and Excel and PowerPoint add-ins around it. It is adding AI features and agents (Generative Search, Smart Summaries, Deep Research and workflow agents), but they run on AlphaSense’s own content inside its own platform, and access from outside agents remains closed. Its MCP connector is in beta, requires an active AlphaSense subscription, has to be added by an administrator, and, according to its own documentation, does not pass full broker research through to the assistant.

Distilla is AI-native. Distilla is the fundamental research layer for AI agents. It was designed from the start as an MCP server, so an agent can pull exactly the data it needs, in a consistent structure, across many companies at once. You add it as a connector in Claude, ChatGPT, Claude Code, Cursor or WorkBuddy, and ask questions in the same chat you already use for everything else. Developers call the same tools over an HTTP API.

The difference matters more than any single feature. With AlphaSense, the platform is where the work happens. With Distilla, the agent is where the work happens, and Distilla supplies the evidence.

Side-by-side comparison

Where AlphaSense wins

AlphaSense leads in two kinds of content, and they are real leads.

Expert calls. AlphaSense has more than 300,000 investor-led expert call transcripts, built up through its acquisition of Tegus in 2024. Distilla does not offer an expert call library. If channel checks and former-employee interviews are central to how you research, this alone may decide it.

Full research reports. AlphaSense gives customers with the right entitlement the full broker reports, from more than 1,000 sell-side and independent firms. Distilla provides summaries of the reports in its library to support agentic analysis, not the full documents.

Your own content and private companies. AlphaSense can search a firm’s internal documents alongside its external library, and it covers private companies and markets well beyond the ones Distilla covers.

Where Distilla wins

Distilla’s case rests on being AI-native, on price, and on the range of data it puts behind one connector.

Built for agents. Distilla was designed as an MCP server for agentic analysis. An agent can scan many companies in one question, get data in a consistent structure, and combine it with its own analysis. AlphaSense remains a platform for manual reading, with agent access still closed.

Institutional rigor, lower entry barrier. There is no sales conversation and no firm-level contract. A free plan and paid plans from $9.90/month put a research layer within reach of individual investors and small teams, not only funds, where an AlphaSense seat typically costs tens of thousands of dollars a year. The data also powers Distilla’s enterprise product for funds.

More data types behind one connection. The same connector returns: - Narrative: sell-side and podcast summaries, filings, earnings-call transcripts and company events. - Structured qualitative datapoints: earnings summaries, business drivers, segment performance, customer and supplier concentration, and MD&A topics extracted over 12+ historical quarters. - Quantitative data: daily prices, financial statements, consensus estimates, valuation multiples and AI-extracted segments and industry-specific KPIs.

An agent can check a broker’s argument against the numbers, and a management comment against the drivers, without leaving the chat.

It explains price moves and holds company knowledge. Distilla links each price move of 3% or more to the dated events behind it. It builds each explanation by ingesting news on the company, extracting and classifying dated events, summarizing earnings when a report is involved, and searching social media for sentiment. Because every move is dated and explained, an agent can scan every big move over the last week, or study all of a company’s moves over 52 weeks, which is not practical with web search. As of 7 October 2026, Distilla’s database holds 438K+ explained price moves, 180K+ sell-side research summaries and 11K+ investor podcast episodes, with about 50,000 company events added weekly. Its causal profiles cover 1,158+ companies across the US, China, Japan, Hong Kong and Korea.

Podcasts are searchable. Investor podcasts carry a lot of candid opinion that never makes it into written research. Distilla holds 11K+ investor podcast episodes, so those views can be searched and cited like any other source.

Asia is built in. For liquid stocks in the US, Japan, Hong Kong, Korea and China A-shares, Distilla covers the companies most investors actually trade, and the sell-side library includes research from twelve Chinese brokers alongside the global banks.

A worked example: the sell-side and podcast view on Meta

To see what this looks like in practice, we asked Claude, with Distilla connected, what sell-side analysts and investor podcasts had said about Meta over the past month.

Claude with the Distilla connector, summarizing a month of sell-side views on Meta (7 October 2026).

The answer opened with the overall picture: coverage had been uniformly positive, driven by the launch of Muse, Meta’s personal AI agent app, with no Sell or Neutral ratings in the period. It then went broker by broker, with dates. J.P. Morgan upgraded Meta from Neutral to Overweight on 10 September and raised its target from $640 to $820, then lifted it to $920 on 24 September. Morgan Stanley had Meta as an Overweight Top Pick with a $775 target. Goldman Sachs reiterated Buy at $725, and Citi rated it Buy at $800 with an Upside 90-Day Catalyst Watch. We checked each of these ratings and targets against the underlying reports in Distilla’s library.

The bear case came mostly from podcasts, which is exactly where a broker-only search would miss it.

The podcast half of the same answer: bullish and bearish views, by show and date.

On CNBC’s Fast Money on 24 September, Dan Nathan called Meta’s glasses hardware “junk” and suggested taking profits. On the Intrinsic Value Podcast on 27 September, the hosts laid out a bear case built on capex and free cash flow. Claude also flagged that the library returns summaries rather than full broker text, so ratings and targets are as the summaries report them.

In AlphaSense, an analyst would answer the same question inside the platform, reading the full broker reports and adding expert calls. Through AlphaSense’s MCP connector, full broker content is not available to the assistant. The trade-off is depth in full documents against an agent-ready, structured layer at a fraction of the cost.

Is Distilla an AlphaSense alternative?

For most agentic research on liquid US and Asian stocks, yes. If you want seamless data across quantitative, qualitative and narrative layers, delivered to an AI agent, Distilla is a strong option at a much lower entry price.

It is not a replacement if your process depends on expert calls, full research reports or searching your own internal documents. In that case, AlphaSense and Distilla can sit side by side: AlphaSense in the browser for document depth, Distilla in the agent for structured, cross-company analysis.

FAQ

What is AlphaSense?

AlphaSense is an AI-powered market intelligence platform sold to funds and large enterprises. It combines broker research, expert-call transcripts, filings, earnings transcripts and news in one searchable platform, with AI search and summaries that return cited answers. It is built for analysts reading and searching by hand.

Is Distilla an AlphaSense alternative?

For most agentic research on liquid US and Asian stocks, yes. Distilla is AI-native, available self-serve with a free plan and paid plans from $9.90/month, and combines narrative, structured qualitative and quantitative data. AlphaSense is the stronger choice for expert calls, full research reports and internal content.

What is the best AlphaSense alternative for individual investors?

AlphaSense is sold to funds through a sales team and does not publish its pricing. For an individual investor or small team that wants a research layer for Claude or ChatGPT without a sales call, Distilla is built for that, with a free plan and paid plans from $9.90/month. Other self-serve data servers, such as FMP and Finnhub, offer filings and transcripts but not sell-side or podcast summaries, structured qualitative datapoints or price attribution.

How much does AlphaSense cost compared with Distilla?

AlphaSense is sold as an annual enterprise subscription and does not publish its pricing. In our understanding, a seat typically costs tens of thousands of dollars a year. Distilla's plans are published: a free Lookout plan, then Scout at $9.90/month, Explorer at $29/month and Navigator at $249/month, plus a custom firm licence.

Is AlphaSense built for AI agents?

AlphaSense is built for analysts reading and searching in its platform. It is adding AI features and agents, but they run inside its own platform. Its MCP connector is in beta, requires an active subscription and an administrator to add it, and does not make full broker content available. Distilla was designed from the start as an MCP server for agentic analysis.

Does Distilla include full broker reports?

No. Distilla provides summaries of sell-side research to support agentic analysis, not the full report text.

Does Distilla have expert call transcripts?

No. Distilla does not offer an expert call library. AlphaSense reports more than 300,000 investor-led call transcripts.

What data does Distilla have that AlphaSense does not?

Distilla adds structured qualitative datapoints (earnings summaries, business drivers, segment performance, customer and supplier concentration, and MD&A topics extracted over 12+ historical quarters), investor podcast summaries, company knowledge and price attribution, and a full quantitative layer (valuation multiples, financial statements, consensus estimates and AI-extracted KPIs). AlphaSense’s strengths are expert calls and full research reports.

Can I use AlphaSense inside Claude or ChatGPT?

AlphaSense offers an MCP connector for MCP-capable chat clients. Its documentation says the connector is in beta, requires an active AlphaSense subscription and an administrator to add it, and does not make full broker content available through the connector.

Can I use AlphaSense and Distilla together?

Yes. They do different jobs: AlphaSense for deep document research, Distilla inside your AI agent.

Which one covers Asian stocks?

Both cover Asia. Distilla’s core coverage is the most-followed, liquid companies in the US, Japan, Hong Kong, Korea and China A-shares, and its sell-side library includes twelve Chinese brokers. AlphaSense describes its research coverage as spanning North America, EMEA, APAC and Latin America.

How do I connect Distilla?

Read-only MCP server at https://api.distilla.ai/mcp. Add it as a connector in Claude or ChatGPT; there is a free plan, and paid plans start at $9.90/month.

Is this investment advice?

No. Distilla is a research tool, not investment advice. The Meta example summarizes published views and is not a recommendation.

About Distilla

Distilla brings institutional rigor to individual investors and small teams. It is the fundamental research layer for AI agents: why stocks move, not just where. The same data powers an enterprise product, including an agent, used by some of the world’s top funds, and is also packaged as a self-serve product so individuals can work from the same facts. It is an MCP server and HTTP API that gives Claude, ChatGPT and your own agents quantitative data, qualitative research and structured company knowledge in one queryable, read-only layer.

•           Quantitative: financial statements, analyst consensus, valuation history and company metrics, including AI-extracted segments and industry-specific KPIs.

•           Qualitative: earnings-call and filing commentary, 180K+ sell-side research summaries and 11K+ investor podcast episodes.

•           Company intelligence: 1,000+ company knowledge topics, business drivers updated quarterly, company events (about 50,000 added weekly), products, peers and sector relationships, and 438K+ explained price moves of 3% or more.

Core coverage is the most-followed companies in the US, Japan, Hong Kong, Korea and China A-shares; sell-side and podcast summaries extend beyond the core universe. Read-only MCP server at https://api.distilla.ai/mcp, with the same lookups over an HTTP API. Works with Claude, ChatGPT, Claude Code, Cursor, WorkBuddy and Doubao. Self-serve: free plan, with paid plans from $9.90/month. Enterprise: contact Distilla. Distilla is a research tool, not investment advice. Figures are as of 7 October 2026.