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Connect Bigdata.com to Claude, ChatGPT, or Copilot in one click. Every answer is grounded in earnings transcripts, premium news, filings, and broker research, with a citation you can actually check.
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Your LLM is confident.
That's not the same as correct.
Ask Claude or ChatGPT a financial question without grounding and it is working from two things: training data that is already stale, and a web search that skims whatever ranks rather than what is authoritative. For anything touching a live earnings call, a filing, or an analyst's actual words, that is a gap you cannot afford.
From question to cited answer
in three moves.
Connect
Add Bigdata as a connector inside Claude, ChatGPT, or Microsoft Copilot. No API keys, no glue code, no engineering ticket.
Ask
Start your prompt with “Using Bigdata” and ask your question in plain English: an earnings digest, a competitor brief, a filing summary, a sentiment check.
Get a cited answer
Your assistant searches transcripts, filings, premium news, and broker research, then answers with inline citations back to the original source.
Using Bigdata, compare Microsoft's last three earnings calls: how guidance language changed quarter over quarter, and how named analysts pushed back in Q&A.
Across the three calls the Azure guide moved up — about 37% cc for Q2 1, 37–38% for Q3 2, then 39–40% for Q4 3. The more telling change is the language around it. In October the constraint was framed as lasting “through at least the end of our fiscal year” 1; by April it had become “at least through 2026” 3. In January management reframed the number itself as “an allocated capacity guide,” noting that had all newly-onlined GPUs gone to Azure “the KPI would have been over 40” 2. Q3 landed at 40%, 39% in constant currency 3. Calendar-2026 capex guidance reached roughly $190bn, about $25bn of it attributed to higher component pricing 3 — the gap Bernstein's Mark Moerdler pressed on that call, asking why capex is growing faster than revenue 3.
Recorded 24 Aug 2026. Figures as reported by the cited documents. Not investment advice.
Millions of entities,
all connected.
Entities such as companies are linked to their units and subsidiaries, down to factories and locations, mapped continuously so a query can follow the connections, not just match keywords.
Entities
Documents
Of history
One connector.
The entire financial record.
Every source is indexed, enriched, and linked by company, so your assistant isn't guessing which document matters.
Earnings transcripts
FullCall historyGuidance calls, analyst Q&A, and investor meetings — not just the press release.
Premium news
200+Licensed sourcesFinancial Times, MT Newswires, Benzinga, The Economist, Alliance News and more, since 2000.
Broker research
100+Research providersNamed-analyst notes from major and non-Western houses.
Filings
90k+Companies · 50+ countriesSEC filings plus international regulatory filings, as published.
Expert networks
200+New interviews / yearPrimary research and specialist commentary via Knowledge Ridge.
Corporate comms
25k+Companies coveredAnnual reports, proxy statements, shareholder letters, M&A announcements, ESG disclosures.
Podcasts
4.4k+Curated showsFinancial and market commentary, transcribed in real time.
Your own documents
∞UploadsSearch your files alongside everything else, in the same conversation.
Grounded, findable,
and cheaper to run.
Stop the hallucinations.
Ground any model in high-quality context. Every answer traces back to a real source, so your agents reason on facts, not guesses.
Built to be found.
Every source is indexed and discoverable. Send a query; Bigdata.com retrieves the most relevant passages to answer it, drawing on 25+ years of content.
Cut the cost of inference.
Precise retrieval means smaller context windows and fewer input tokens, so the cost of AI stops ballooning and starts falling.
Built for the questions that actually
move your work forward.
Read every 10-K so you don't have to.
Point your assistant at a company and it pulls the filings, transcripts, and estimates that matter, ranked and cited.
“Using Bigdata, compare this company's last three earnings calls. Show how guidance language changed quarter over quarter, which topics management stopped volunteering, and how named analysts pushed back in Q&A. Flag any metric that was redefined. Output as a short memo with inline citations.”
- TranscriptGuidance language, quarter over quarter· Last three calls
- FilingSegment performance against consensus· As reported
- Broker researchNamed-analyst reaction, not aggregate sentiment· Same week
Every line traces back to a source you can open. Where the evidence isn't there, it says so instead of filling the gap.
Know their move before the press release.
Track rivals across media, hiring trends, and expert calls to catch a strategy shift while it's still a signal.
“Using Bigdata, track how a named competitor's strategy language has shifted over the last six months across premium news, expert interviews, and regulatory filings. Separate confirmed announcements from directional signals, and tell me where sources disagree. Output as a timeline with citations.”
- TranscriptStrategy language that quietly changed· Last two quarters
- Expert networkA third-party read from people close to the market· Recent interviews
- FilingRegulatory disclosures, as published· As filed
Every line traces back to a source you can open. Where the evidence isn't there, it says so instead of filling the gap.
Catch the narrative before consensus does.
Surface emerging themes and sentiment swings across the document set while there's still room to act.
“Using Bigdata, identify the themes gaining momentum across this sector for the current quarter. Rank them by how much coverage has accelerated rather than by raw volume, name the companies driving each one, and separate genuine shifts from single-source noise. Output as a ranked list with citations.”
- Premium newsThemes ranked by acceleration, not volume· This quarter
- TranscriptSentiment shift broken down by company· Latest calls
- PodcastCommentary you would not have read in time· This week
Every line traces back to a source you can open. Where the evidence isn't there, it says so instead of filling the gap.
Walk into the call already knowing what they care about.
Generate a live, sourced brief on any prospect (earnings, risks, priorities) in seconds.
“Using Bigdata, build a pre-call brief on a named prospect: latest reported results, the priorities management has stated publicly, and any operational pain points they flagged themselves. Note anything a direct competitor of theirs announced recently. Output as five bullets with citations.”
- TranscriptStated priorities, quoted from the call· Latest call
- FilingRecent results and revisions· As reported
- Premium newsPublic pain points worth opening with· Last 30 days
Every line traces back to a source you can open. Where the evidence isn't there, it says so instead of filling the gap.
We send the signal.
And leave the noise out.
Grounded answers,
benchmarked.
Independent evaluation of Claude's answers with and without the Bigdata connector shows measurable gains in the areas that matter most for financial research:
| Evaluation dimension | Claude (web search only) | Claude + Bigdata |
|---|---|---|
| Factual accuracy | 7.5 | 9.0 |
| Source quality & attribution | 7.5 | 9.5 |
| Completeness & coverage | 8.5 | 9.0 |
| Analyst coverage quality | 7.5 | 9.0 |
| Overall average | 8.4 | 8.8 |
Web search still edges ahead on stylistic dimensions like structure, readability and polish; showing that honestly builds trust.
Already where
you already work.
Add the connector once and it follows you across every assistant you use.
You're two minutes from
your first grounded answer.
1
Create a free account. No credit card required.
2
Free credits are applied to your account automatically.
3
Add Bigdata as a native app or connector in Claude, ChatGPT, MS Copilot.
4
Start any financial prompt with “Using Bigdata” and ask away.
Remember: once connected, start your prompt with “Using Bigdata” so your assistant knows to search the grounded index instead of guessing.
Built for institutions that
can't afford to guess.
Financial institutions can extend the same connector across an entire agentic platform, with SOC 2 Type II, ISO 27001, data residency controls, and a guarantee that your data is never used to train models.
Stop guessing.
Start citing.
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