Real Archives. Real Deal Mechanics.
Not sure whether your organization's data qualifies? Choose a company below to see the sample they shared first, what the full dataset contained, why it was valuable, and how the deal was executed and paid.
Anonymized case studies. Company names and identifying details have been changed to protect client confidentiality. Each profile is a composite of several engagements and typical deals in that industry; payout figures are illustrative.
Case Studies
Choose a case study
Select a company to see its full case study.
- Read the Aster Cloud case study
- Read the Redwood Peak Partners case study
- Read the Hawthorne & Vale LLP case study
- Read the Crescent Health Partners case study
- Read the Helios Ridge Energy case study
Aster Cloud · SaaS & Technology: Enterprise data infrastructure SaaS company with 6.5 years of connected Slack, CRM, support, Jira, telemetry, and finance history.
Aster Cloud
Enterprise data infrastructure SaaS company with 6.5 years of connected Slack, CRM, support, Jira, telemetry, and finance history.
- Scale
- 193 employees · $58M run-rate
- Archive span
- 6.5 years
- Seller payout
- ~$675K
- Time to payout
- 30 days
01 · Company Profile
1 — Company Profile
Overview
Aster Cloud — Enterprise data infrastructure SaaS. Founded 2019. Aster Cloud had unusually connected operating history across Slack, CRM, support, Jira, product telemetry, finance models, and document revisions.
Scale
193 employees · $58M run-rate. Archive: 6.5 years · 11.8 TB raw · 8.4M records.
02 · Data Profile
2 — Data Profile & Valuation Drivers
Initial Sample Data
System inventory + 3 months of two Slack channels + 250 support tickets + 500 Jira issues + a customer-health export + 20 representative Drive files. Approx. 4.8 GB sample.
Full Dataset Delivered
| Source | History | Scale | Format | Approx. size |
|---|---|---|---|---|
| Slack | 6.5y | 193 users | 4.1M msgs | 38 GB |
| Gmail | 6.5y | 205 boxes | 7.8M msgs | 210 GB |
| Google Drive | 6.2y | 41K files | Docs/Sheets | 184 GB |
| CRM | 5.8y | 184K recs | CSV/API | 9 GB |
| Support | 5.9y | 96K cases | JSON/CSV | 18 GB |
| Jira | 6.1y | 142K issues | JSON | 11 GB |
| Product events | 4.7y | 3.2B events | Parquet | 1.9 TB |
Scroll sideways to see all columns.
Also included: finance/planning (2,840 files), contracts with revisions (7,400 docs), and docs/presentations (41K files). Metadata profile: identity mapping high, revision history preserved, timestamps normalized, attachments linked, sensitive data filtered.
Valuation Rationale
Why this company was interesting
Stable account IDs and incident IDs made it possible to connect customer problems to internal decisions, engineering work, and commercial outcomes.
What drove value
Cross-system identifiers, revisions, customer-level outcomes, technical incident trails, and enterprise commercial context. The dataset showed how software teams diagnose problems, make decisions, change products, and observe commercial outcomes.
Data categories and why each was useful
- Slack / internal comms · 4.1M msgsreasoning + decisions
- CRM + customer history · 184K recscommercial outcomes
- Support tickets · 96K casesproblem → resolution
- Jira / incidents · 142K issuestechnical work trails
- Product telemetry · 3.2B eventsbehavior + outcomes
- Finance / planning · 2,840 filesforecasting / decisions
- Contracts / revisions · 7,400 docscommercial context
- Docs / presentations · 41K filesknowledge + revisions
What would have made this archive weaker
A one-year Slack export from a six-person startup; final PDFs with no revisions; duplicate backups; public marketing files; or logs that cannot be linked to customers or outcomes.
03 · Deal Execution
3 — Execution, Deal Structure & Economics
Timeline
From sample submission to payout: 25 days
From first contact to payout: 30 days
Day 0
First contact
Day 2
Seller intake
Day 5
Sample export
Day 9
Technical / rights review
Day 14
Buyer evaluation
Day 19
Commercial indication
Day 25
Full export
Day 28
Acceptance
Day 30
Seller payout
Timelines may vary based on the data.
Ingestion & Extraction
Aster Cloud delivered the export directly from its own systems. The deal included a preparation and diligence phase covering extraction, QA, and rights review. The full export (Day 25) preserved source files plus metadata, timestamps, formulas, threads, and relationships. On receipt, Input Frontier handled filtering, normalization, and QA before acceptance.
Transaction Type
Non-exclusive license of a defined data package. The seller kept its underlying business.
Seller Compensation
~$675K
Illustrative figure · client anonymized
The Process
How the Process Works
01
Introduction & Intake
Tell us about your organization: years in operation, rough headcount, major systems (Slack, Google Workspace, CRM, Jira, industry software), how long records are retained, and whether you control them. Exact storage numbers are not required up front.
02
Small Representative Sample
Share a small, representative slice so we can see the structure, metadata, and how your systems link together. In the case studies, samples ranged from about 3 GB to 18 GB and arrived 5–13 days after first contact.
03
Technical & Rights Review
We confirm you have authority to license the records, check how many years are continuous and whether records link across systems, and decide what must be excluded for privacy, privilege, confidentiality, or third-party rights. Regulated archives (legal, healthcare) add a formal privilege or privacy protocol at this stage.
04
Valuation & Commercial Terms
Value depends on historical depth, volume, expertise and rarity, reasoning density, workflow richness, cross-system linkability, revisions, outcomes, completeness, rights, extraction difficulty, and privacy constraints. It is not based on gigabytes alone. You then receive a commercial indication.
05
Full Export, Filtering & QA
Inventory → Extract (keeping metadata, timestamps, formulas, threads, and relationships) → Filter out restricted material → Normalize → QA for completeness, broken links, missing attachments, duplicates, and time coverage → Deliver.
06
Acceptance & Payout
Once the delivered dataset is accepted, payment follows. In every case study, payout arrived 1–2 days after acceptance. Total time from first contact to payout ran from 28 to 36 days across all five case studies.
What makes an archive stronger
- Roughly 5+ years of operating history
- Roughly 10+ employees
- Multiple systems that can be linked by timestamps or IDs
- Preserved revisions and outcomes
These are heuristics, not hard minimums. A smaller archive can still be valuable if it is unusually expert, rare, longitudinal, dense, or well-linked.
Does Your Organization Look Like One of These?
Tell us about your systems and history. We'll help with the audit, sample, valuation, and extraction plan.
Or email us directly at team@inputfrontier.com
Anonymized case studies. Company names and identifying details have been changed to protect client confidentiality. Each profile is a composite of several engagements and typical deals in that industry; payout figures are illustrative.