Solution · RevOps and GTM operations

Add useful company context without creating more CRM cleanup.

Start with CRM records or any company list. Choose the public conditions your teams need for segmentation, routing, or account research. Kaiju resolves companies, keeps your existing IDs and operational fields attached, and returns supported findings with uncertain matches and incomplete checks clearly marked.

Analyze 25 companies See example findings

Existing IDs, owners, stages, and segments preserved
Company and website matches remain reviewable
Findings include sources, dates, and result status
Your team controls what returns to the CRM

What your team receives

A reviewable CRM update

See the original record, resolved company, added findings, and review status together before anything is imported.

Original record: CRM ID, owner, lifecycle, territory
Company match: company, website, match status
Added findings: selected conditions, source, observed date
Import decision: approve, correct, exclude, or hold

Start: Provide the companies you want to investigate using company names, websites, or both.
Check: Kaiju checks public sources and records what it observed, where it found it, and which checks were inconclusive.
Review: Review the findings and supporting evidence, filter the results, and download them with your original company information intact.

Protect the records your teams trust

Add company context without creating a second source of truth.

Kaiju works with the records you already maintain. It preserves the fields your team owns, adds supported public findings beside them, and keeps uncertain cases separate from clean results.

Keep trusted fields intact

Preserve CRM IDs, owners, lifecycle stages, territories, segments, and other operational fields through review and download.

Resolve the right company

Use available company names, websites, email domains, and stable IDs to identify the most likely company and public website behind each record.

Separate exceptions from clean records

Keep ambiguous matches, incomplete checks, contradictory evidence, and unresolved records visible instead of flattening them into blanks.

Useful data, not a larger data dump

Add only the findings your GTM workflows can use.

Choose the public conditions and supporting context needed for segmentation, routing, research, or handoff before the results return to your systems.

Define the fields that matter

Select the technologies, categories, conditions, dates, and result fields that support a real downstream workflow.

Keep the evidence attached

Retain the supporting source, observation date, and review status so downstream teams can understand what each finding means.

Control what gets imported

Review uncertain matches and incomplete checks separately, then return only the approved fields and records to the CRM.

How it works

Review every change before it returns to your systems.

Kaiju currently delivers a CSV, giving your team a controlled path from source records to approved updates without automatic CRM writeback.

01
Provide the records
Start with a CRM export or any company list. Kaiju keeps the original rows, IDs, owners, and operational context attached.
02
Resolve and investigate
Kaiju proposes company and website matches, flags duplicates and uncertain records, and checks public sources for the selected conditions.
03
Review and return approved updates
Inspect familiar records, correct exceptions, and download the approved findings with the original CRM IDs and record context preserved.

Better GTM operations

Give revenue teams company data they can use and RevOps can trust.

Create a stronger starting point for segmentation and account research while keeping the original record, supporting evidence, and uncertain cases visible.

More reliable segmentation

Group companies using explicit public conditions with documented handling for missing, unclear, or incomplete results.

Cleaner team handoffs

Give sales, marketing, and research teams consistent company context without making them interpret unexplained fields or scores.

Faster exception review

Route ambiguous company matches, incomplete checks, and questionable findings for review without holding back clean records.

Evidence before action

Check why a finding is supported before your team uses it.

Open any result to see what Kaiju found, where it found it, when it was observed, and whether the check was complete. Unclear and incomplete results remain visible instead of being silently converted into confident answers.

See how Kaiju produces a field

Company match
See which company and website Kaiju connected to the original row.
Returned finding
See the value Kaiju added and whether it is supported, unclear, incomplete, or unresolved.
Supporting source
Open the public page or observable signal behind an important finding.
Check status
See when the research happened and whether anything prevented Kaiju from completing it.

See how the same intelligence supports another team.

Each team starts with companies it already cares about. The file, terminology, and way the findings are used change with the team.

B2B technology vendors

Find companies with tech stacks relevant to your product and review the evidence behind each match.

See the solution

Agencies and technology partners

Research technology environments across client and prospect lists without repeating the same website checks by hand.

See the solution

Browse solutions

Start with companies you already care about

Test the workflow with records your team already knows.

Include clean records, duplicates, known mismatches, and uncertain cases so your team can assess company resolution, returned findings, supporting evidence, and import behavior before increasing volume.