§ 01 · Features
Finance tools shaped for agent context.
Finterm gives agents both the raw financial data and the token-efficient layer on top: filtered sources, calculated signals, diffs, and structured outputs.
Ticker data bundle
finterm bundle run ticker_data NVDA --delivery-mode inline_result
Creates the NVIDIA ticker_data run and returns the structured ticker snapshot inline.
The full ticker snapshot in one bundle: earnings, guidance, price reaction, ratios, options sentiment, short pressure, technicals, statements, and pre-earnings context.
SEC filing diffs
finterm tool sec_filing_diff NVDA --base 2025:Q3 --compare 2026:Q1
Compares NVIDIA filings section by section and returns the changed language.
MD&A · 131% churnRisk Factors · 60% churnQA-checked
Ticker Deep Research
finterm bundle run company_deep_research NVDA --company-name "NVIDIA Corporation" --param q=Q1 --param fy=2027 --param prev_q=Q3 --param prev_fy=2026 --delivery-mode summary_json
Runs the search, crawl, dedupe, and source-labeling pass for NVDA.
Thorough by design: fetches 600–800 links per ticker, then strips the 30–40% that is noise—AI slop, SEO spam, syndicated reprints—leaving a comprehensive read of what the market thinks about the stock.
40 searches · 742 sources crawled · 272 dropped as noise, dupes, and off-topic
Options sentiment
finterm tool options_overview NVDA
Reads the live options chain into put/call flow, IV30, and expected moves.
Neutral-bullish Call-tilted flow · IV30 below realized vol
Insider and 13F flows, netted
finterm tool insider_trades NVDA
Returns NVIDIA Form 4 insider transactions with the trailing 90-day open-market net.
Ticker sentiment
finterm tool ticker_sentiment NVDA
Scores seven components against NVDA’s own trailing year and returns the 0–100 composite.
0
extreme fear up from 6 a week ago · Δ5d +8.2
coverage 5/7
§ 02 · Why it exists
Finterm connects the data first, so your agent can reason next.
It turns the messy inputs behind a trade into sourced, timestamped outputs: ticker data, filing diffs, ownership flows, market context, and deep research with the noise stripped.
One command
Give your agent a question and let the CLI pull the relevant financial context.
Agent-readable output
Results come back as structured data your agent can read, cite, and reuse.
Sources included
Facts carry source links, timestamps, and caveats instead of loose summaries.
§ 03 · Full demo
One prompt. Three filers. The pattern hiding in plain sight.
A real run: the prompt, your agent’s sourced answer, and the exact
finterm calls underneath.
finterm sec_filing_diff · GOOGL · AMZN · MSFT
can you use finterm to pull SEC filing diffs for the big cloud providers (google cloud, aws, microsoft) and find any patterns they all mention? just the last 4 quarters of 10-Qs
Mapped the three cloud brands to their SEC filers (Alphabet/GOOGL, Amazon/AMZN, Microsoft/MSFT) and diffed consecutive 10-Qs section by section.
Four themes show up across all three filings:
- An AI-capex step-change. All three roughly doubled
quarterly capex year over year, tied explicitly to AI infrastructure.
“During the three months ended March 31, 2025 and 2026, we spent $17.2 billion and $35.7 billion on capital expenditures, respectively.” Alphabet 10-Q · FY2026 Q1 · MD&A
- AI written into the risk factors. Each amended
long-standing risk language to name AI as a new vector.
“…building AI-optimized infrastructure, including our custom TPUs… Our investments ultimately may not be commercially viable or may not result in an adequate return of capital.” Alphabet 10-Q · FY2026 Q1 · Risk Factors
- Multi-billion stakes in frontier-AI labs. The build-out
now runs through the model labs themselves.
“In Q1 2026, we invested $15.0 billion in OpenAI’s Series C Preferred Stock and entered into an equity commitment letter agreement to purchase an additional $35.0 billion…” Amazon 10-Q · FY2026 Q1 · MD&A
- Off-balance-sheet data-center and power exposure. Growth
leans on uncommenced leases and credit backstops for infrastructure they
don’t own.
“…up to $33.3 billion of future backstops to support the build-out of data center and energy supply infrastructure, alongside uncommenced data-center leases of $75.6 billion.” Alphabet 10-Q · FY2026 Q1 · MD&A
Net: across Google Cloud, AWS, and Azure, the last few quarters of 10-Qs converge on a capital-intensive AI build-out that is now visible in both the financials and the risk language. Every quote links to the exact filing.
Real Finterm output · figures quoted from public filings Not investment advice
§ 04 · Prompts to try
Point your agent at the hard questions.
The same shape: your prompt, then Finterm’s sourced answer, across the questions a serious analyst asks.
Is this dip in NVDA being bought or sold by insiders? Pull Form 4 activity and the latest 13F holders, and net it out.
Give me the bull and bear case on AMD’s data-center demand this quarter, from multiple sources, deduped and labeled primary or secondary.
What’s the options market pricing into TSLA earnings, and where does sentiment sit versus its own trailing year?
Diff Apple’s latest 10-K against last year’s and flag every new or softened risk factor.
§ 05 · Everything in the bundle
Everything in the bundle—and what it costs bought separately.
One subscription replaces four or five. The comparison, category by category—including the rows you can buy elsewhere.
In the bundle Comparable cost
The company packet. Earnings, guidance, price reaction, ratios, options, short pressure, technicals—one call. $60–150/mo
SEC filing diffs. Section-aware, line-by-line diff of any two filings, churn stats, QA-checked. No real equivalent
SEC search and sections. Find any filer’s filings; pull clean narrative sections as text. $49/mo
Ownership flows, netted. Form 4 trades rolled into a 90-day open-market net; 13F holders, ticker-mapped. $49–149/mo
Options intelligence. Implied versus realized with rank, today’s flow, positioning, expected moves—one call. $99–199/mo
Sentiment as a number. A 0–100 composite of trend, flow, and positioning, each scored against the ticker’s own year. $59–99/mo
Ticker Deep Research. 600–800 links per ticker filtered into one research packet: noise stripped, reprints merged, sources tiered, provenance kept. No real equivalent
Prices and statements. Live prices, reported financial statements, standard technicals. $20–99/mo
The dataroom. Every run cached to a local, re-queryable room — produced once, reused every session. No real equivalent
Purchased separately: $300–450/month (APIs alone)
Finterm Pro: $200/month (fetched data cached, yours to keep)
Category price ranges from published provider price lists, as of July 2026.
Give your agent a finance brain.
$150/month
$200/month
3-day free trial
3-day free trial, card required.
Special preview price for the first 1,000 users: $50 off for a limited time during the preview period.
Once you have an account, just give finterm to your favorite
coding agent:
In your terminal
npm install -g @finterm-ai/cli
Or paste into your coding agent
I want to set up finterm.ai: run `npm install -g @finterm-ai/cli`, then `finterm setup` to install your agent skills and `finterm prime` to orient yourself. I’ll handle the browser step of `finterm auth login` when you’re ready—then show me what Finterm can do.
Not investment advice.