The full terrain of material corporate activity, structured across every public company.

The full terrain of material corporate activity, structured across every public company.

The public record has never been visible at this resolution.

The public record has never been visible at this resolution.

For humans and AI agents alike.

For humans and AI agents alike.

Industry patterns appear when you structure every detail

01

Thousands of unscheduled disclosures, structured moments after they're filed.

10-Ks and 10-Qs arrive on a predictable schedule in consistent formats. That data is well covered. 8-K filings capture the actual velocity of a company, filed within days of a material event, with over two decades of history in the EDGAR archive. We structure the activity once it happens, not months later when it's aggregated into a 10-K.

02

The whole market, not just the top.

Existing coverage focuses on large-cap issuers using human analysts. For small and mid-cap companies, this depth of analysis is much harder to come by. Our agents cover the full universe of public filers.

03

We structure the activity and the landscape it forms.

Our agents work like analysts, not summarizers. They research every filing and its exhibits to find the details that matter, structuring material activity the same day it's disclosed. The details live in exhibits that run hundreds of pages of dense legal text, staggered across multiple filings over time, with every company structuring them differently. Critical properties are identified and pieced together as they emerge across filings, maintaining a persistent record of the full lifecycle as it evolves. Together, they reveal the full terrain at scale.

Novel layers of financial data

Structured signals from dense filings, across every public filer

event_type: covenant_waiver
company: Coreline Medical Holdings, Inc.
ticker: CMED
sub_sector: Healthcare Services
lender: Driftwood National Bank, N.A.
lender_type: bank
principal: 22000000
covenants_waived:
  - {type: leverage_ratio, threshold: 4.50, actual: 5.82}
  - {type: fixed_charge_coverage, threshold: 1.20, actual: 0.87}
waiver_number: 3
duration_days: 64
going_concern: false
conditions: [covenant_tightening, fee, reporting_requirement]
...
Reading between the lines

The exhibits are where the real detail lives, hundreds of pages of dense legal text that every company structures differently. Our engine develops familiarity with the language over time, learns what to look for, distinguishes between events that look similar on the surface but carry very different consequences, and finds the specific values that matter buried deep in the contracts.

event_type: debt_default
company: Broadleaf Industrial Corp.
ticker: BLFC
sub_sector: Industrial Machinery
trigger_type: missed_payment
acceleration_demanded: true
missed_amount: 812500
lender: Atlas Commercial Finance, LLC
lender_type: specialty_lender
instruments:
  - {name: Senior Secured Term Loan, principal: 8200000, default_source: primary}
  - {name: Revolving Credit Facility, principal: 3200000, default_source: cross_default}
total_exposure: 11400000
connected_forbearance: broadleaf-atlas-forbearance-2025-08
...
The macro view

Individual events are useful. Thousands of them structured across every public filer reveal something different entirely: industry patterns, lender behavior, concentration risk, and trends that only become visible at scale. The engine runs continuously, same day, so the landscape is always current.

event_type: forbearance
company: Solarus Energy Holdings, Inc.
sub_sector: Oil & Gas
trigger_type: missed_payment
missed_amount: 578125
lender: Greystone Capital Partners, LP
lender_type: private_credit
principal: 12500000
seniority: senior_secured
forbearance_start: 2025-10-31
forbearance_end: 2025-11-14
duration_days: 14
conditions: [payment_requirement, collateral, reporting_requirement]
rate_stepup_bps: 200
...
The connective tissue

A single event can unfold over months of filings. The engine links them into chains, classifies companies by what they actually do rather than outdated industry codes, and traces how terms evolve across amendments and extensions. Multiple systems working in concert to build the full picture that no single filing contains.

Why we're building Terrain

For the first time, the technology exists to see what's actually happening in the world, as it's happening. Not one domain or one industry at a time, but the full landscape of information being disclosed and published every day. The raw material for understanding has always been there. The ability to structure it, connect it, and see the full picture has not.

We've spent the past decade building systems that proved this was possible one domain at a time. We built political reporting tools at the Wall Street Journal that saw what reporters couldn't read fast enough, automated clinical intelligence on the Bloomberg Terminal that was the first of its kind, and provided a tip service for the Associated Press that surfaced local leads to newsrooms around the country. Each one closed a gap between what was happening and what anyone could see.

AI agents will remove the final constraint by doing it all at once. The same principles that worked in one domain can now expand across all of them, simultaneously, continuously, and without the latency that has always separated events from understanding. A force that finally allows a decade of experience to expand across every domain at once.

That is what Terrain is building. SEC filings are where we started. The terrain grows from here.

What the engine surfaces

Structured signals from dense filings, across every public filer

event_type: covenant_waiver
company: Coreline Medical Holdings, Inc.
ticker: CMED
sub_sector: Healthcare Services
lender: Driftwood National Bank, N.A.
lender_type: bank
principal: 22000000
covenants_waived:
  - {type: leverage_ratio, threshold: 4.50, actual: 5.82}
  - {type: fixed_charge_coverage, threshold: 1.20, actual: 0.87}
waiver_number: 3
duration_days: 64
going_concern: false
conditions: [covenant_tightening, fee, reporting_requirement]
...
Information architecture

Our engine identifies what categories of activity exist and determines which properties are consistently disclosed. As the world changes, it adapts.

event_type: debt_default
company: Broadleaf Industrial Corp.
ticker: BLFC
sub_sector: Industrial Machinery
trigger_type: missed_payment
acceleration_demanded: true
missed_amount: 812500
lender: Atlas Commercial Finance, LLC
lender_type: specialty_lender
instruments:
  - {name: Senior Secured Term Loan, principal: 8200000, default_source: primary}
  - {name: Revolving Credit Facility, principal: 3200000, default_source: cross_default}
total_exposure: 11400000
connected_forbearance: broadleaf-atlas-forbearance-2025-08
...
Continuous coverage

Our system runs automatically, same-day, across every public filer. The data grows as new filings arrive.

event_type: forbearance
company: Solarus Energy Holdings, Inc.
sub_sector: Oil & Gas
trigger_type: missed_payment
missed_amount: 578125
lender: Greystone Capital Partners, LP
lender_type: private_credit
principal: 12500000
seniority: senior_secured
forbearance_start: 2025-10-31
forbearance_end: 2025-11-14
duration_days: 14
conditions: [payment_requirement, collateral, reporting_requirement]
rate_stepup_bps: 200
...
Extraction

AI agents read every filing and its exhibits, pulling structured fields from the legal text and connecting related disclosures as they arrive.

Data stories

Deep dives and automated dispatches from the corporate terrain our engine maps across SEC EDGAR.

Get in touch

Get in touch

We cover corporate credit activity across SEC filings today, and the terrain grows from here. If you work with credit data, need to see pattersn across the SEC archive, or have a domain you think deserves this kind of view, we'd like to hear from you.