01 · Robust searching
Beyond keyword
Classifiers built per filing type read the way an analyst would — semantic, not string matching. Ask for a concept and get the passages that mean it.
529 classifiers · 245M sentences
Investment Research
Ask a question across every SEC filing since 1994 and get the answer with the filing, the paragraph and the date attached — so the next person who asks where it came from already has it.
Full-text search returns a list you still have to read. AI summarisers return prose you cannot check. Both leave the analyst doing the same job: opening filings one at a time to find out whether the thing they suspect is actually in there. And then proving it.
What you get instead
what an analyst actually gets back
01 · The question
Which of these 40 companies changed their revenue recognition language?
plain language, across a coverage list
02 · The answer
7 of 40 changed it
each with the filing, paragraph and date attached
not a document list — a finding
03 · The filing
10-K · filed 2026-02-14
Accession 0000320187-26-000032
one click to the exact paragraph
04 · The history
Language tracked 12 quarters
first mention · repeated · restated
01 · Robust searching
Classifiers built per filing type read the way an analyst would — semantic, not string matching. Ask for a concept and get the passages that mean it.
529 classifiers · 245M sentences
02 · Surfaced data
Terms, figures, dates and language pulled out of the document and put in a table — so you compare values rather than re-read paragraphs.
extracted, organised, integrated
03 · Peer analysis
Benchmark one company's disclosure against its peers on the same section, and see what changed between years.
risk factors · MD&A · policies
04 · Connected context
The filing sits next to who owns the company, what the insiders did, and what was announced — resolved to the same entity.
NexusID
The scenario
You cover 25–40 names. Every quarter dozens of filings land within days and you need to know which ones matter before reading a page.
How Kaleidoscope helps
The scenario
You are accountable for what the team publishes. Every number in a note has to be defensible six months later, by someone who did not write it.
How Kaleidoscope helps
The scenario
You are briefed on an industry you did not cover last week and need to be credible on it by Thursday.
How Kaleidoscope helps
Search and compare across every filing type, with the extracted figures in a table beside the language they came from.
Conversational research over every filing, news article and 13F position, backed by the same index — with the sources attached to the answer.
Tell it the language, the figure or the filer you care about, and hear about it when the next filing lands rather than next quarter.
Core platform
Data layers that feed it
Workflow & delivery
| How it compares | Kaleidoscope | Keyword search | AI summarisers |
|---|---|---|---|
| What you get back | An answer with its source | A list of documents | Prose with no source |
| Checking a claim | One click to the paragraph | Read the document | Not possible |
| Across a coverage list | One question, all names | One search at a time | Context window limits |
| Extracted figures | In a table beside the language | Not extracted | Sometimes, unverifiable |
| As-of a past date | Point-in-time, frozen | Current documents only | No concept of it |
Why teams switch
It makes SEC research fun again — I stopped opening twenty filings to answer one question.
Talk to our team about how you work today, or start a trial and explore the platform yourself.