Commercial Diligence Brief
Pre-LOI telemetry on a named acquisition target — un-gameable signals on growth, churn, and adoption.
The Commercial Diligence Brief assembles pre-LOI telemetry on a named acquisition target from sources the target cannot suppress or curate: SEC 10-K risk-factor mining across the target and competitive set, technology adoption trajectory from public surfaces, unfiltered sentiment from review sites and Reddit and Hacker News, GitHub and PyPI activity for software targets, BLS local employment and competitive labor signal, and churn-risk indicators surfaced from public conversation.
The output is a procurement-grade memo: each finding traces to a public source, statistical claims meet validity thresholds, and the Counter-Signal Pass attaches the strongest reason each finding might be wrong. Deliverable is a single PDF report plus companion data files. Base scope covers the target and the competitive set; peer benchmarks are +$1,499 each.
Built for PE firms running diligence, VC partners scoping commitments, hedge-fund research, and corporate M&A teams pressure-testing strategics.
Is this target's market actually growing — and do users love the product, or is there a churn cliff coming?
What buyers actually ask.
Who does pre-LOI commercial diligence with public-signal data?
The Commercial Diligence Brief is the artifact. We assemble pre-LOI telemetry on a named acquisition target from public surfaces — SEC filings, technology adoption signals, unfiltered sentiment, GitHub and PyPI activity, BLS labor signal, churn-risk indicators — into a procurement-grade memo. Findings trace to sources; statistical claims meet validity thresholds.
Is this target's growth real, or is there a churn cliff coming?
The brief surfaces churn-risk indicators directly — review-site sentiment trajectory, Reddit and Hacker News thread density on cancellation themes, GitHub or PyPI activity decay for software targets, hiring slowdown ahead of revenue slowdown. The thesis the report names is the strongest reading of the joined signal.
How is this different from analyst-led diligence at a McKinsey or Bain?
Analyst-led diligence delivers an artifact in the $50–200K range. The Commercial Diligence Brief delivers a comparable artifact at a price that fits a deal's diligence budget. The trade is depth of primary research versus depth of public-signal triangulation; the brief is calibrated for the latter.
What public sources actually go in?
SEC EDGAR (10-Ks, 10-Qs, 8-Ks, S-1s), App Store and Play Store reviews, Trustpilot, G2, Capterra, Reddit, Hacker News, GitHub, PyPI, BLS QCEW and JOLTS, Glassdoor (sentiment only), USPTO, and the target's own marketing footprint. The full source list ships with each report.
What if the target is private and has no SEC filings?
The 10-K layer drops out and the rest of the methodology stays. Private targets carry the heaviest weight on review-site sentiment, hiring signal, technology adoption, and developer-community vitality. Peer benchmarks against public comparables become more important and we recommend adding peers at scope.
How do peer benchmarks add value?
Each peer benchmark adds a comparator company against which the target's signals are read. A target whose review-site sentiment is dropping looks different against a peer set whose sentiment is also dropping (sector headwind) versus a peer set whose sentiment is climbing (target-specific risk).
How long does the engagement take?
Ten to fourteen business days from intake confirmation. Most engagements come in at twelve. Expedited turnarounds for time-sensitive deals are scoped at intake.
The deliverable, in detail.
- SEC 10-K risk-factor mining across the target and competitive set, with the differential analysis isolating target-specific risk from sector risk.
- Technology adoption trajectory across product-tier public surfaces — App Store, Play Store, G2, Capterra, Trustpilot — joined to release cadence.
- Unfiltered sentiment from review sites, Reddit, Hacker News, and Twitter/X (consumer targets), with cross-surface variance read.
- GitHub and PyPI activity trajectory for dev-tool and infrastructure targets, with contributor concentration and package-download cadence.
- BLS local employment and competitive labor signal at the target's operating geographies, with hiring-slowdown lead-time analysis.
- Churn-risk indicators surfaced from public conversation, joined into a single churn-risk read with confidence tagging.
How the report is built.
The Commercial Diligence Brief runs seven layers in parallel against the named target. SEC filings are mined for risk-factor language, customer-concentration disclosures, and management-discussion-and-analysis claims; the same mining is run against the competitive set so target-specific risk is distinguishable from sector risk. Technology adoption is read from product-tier public surfaces — App Store and Play Store activity, G2 and Capterra review velocity, Trustpilot — and joined to release cadence.
Unfiltered sentiment is sourced from review sites, Reddit, Hacker News, and (for consumer targets) Twitter/X. Each surface is scored independently, then joined into a cross-surface read so a divergence between a curated review surface and an unfiltered community surface surfaces as a finding rather than a single number.
For software and infrastructure targets, GitHub and PyPI activity trajectories are computed: commit cadence, issue activity, contributor concentration, package-download trajectory. These signals are predictive at lead times traditional commercial diligence does not access.
BLS QCEW employment data and BLS JOLTS hiring data give a labor-market read at the target's operating geographies. Hiring slows before revenue slows; the labor signal is the early-warning layer.
Churn-risk indicators are surfaced from public conversation — cancellation-theme density on Reddit, support-volume signal from Trustpilot and G2 reviews, app-store one-star theme clusters. A senior analyst reviews and reconciles all seven layers before the report is drafted. The Counter-Signal Pass is run on every finding the brief names.
Counter-Signal Pass is included on every report. The full Foragentis methodology is documented in The State of AEO and GEO in 2026.
What this report does NOT do.
Procurement-grade reports scope themselves. The work below is adjacent and important — and is not in this SKU.
The Commercial Diligence Brief does not replace legal or financial diligence. Public-signal telemetry is one input among several to a full diligence pack; tax, accounting, IP-ownership, and contract review are domain-specialist work the brief does not undertake.
The brief does not include primary customer references or management interviews. Sentiment is read from public conversation. If your diligence motion requires named-customer conversations, scope a separate customer-development engagement.
Findings are stamped with the data window. A target with a major step-change event between report delivery and your decision date — a CEO departure, a regulatory action — is no longer the target the brief described. We say so on the page.
What the engagement costs.
The Counter-Signal Pass — every thesis stress-tested against its strongest opposing case — is included on every report at no extra cost. See the Counter-Signal block on the catalog hub →
Methodology preview on request.
A redacted public sample for this SKU is in production. To preview the methodology now, email forintel@foragentis.com and we will send the methodology one-pager. The published methodology white paper — The State of AEO and GEO in 2026 — covers the underlying analytical framework.
Adjacent reports.
R&D Velocity Audit
How fast a company translates R&D into shipping product, benchmarked against peers.
Technographic & Traffic Teardown
Tech-stack archeology, WHOIS history, 24-month traffic trajectory, same-stack cohort, and historical SERP rank for any named domain.
About Foragentis.
Foragentis is an AI research and product company based in Sacramento, California. ForIntel is the business-intelligence research arm — producing custom dossiers across four buyer lanes: Search & AI Visibility, Markets & Locations, Capital & Innovation, and Specialty.
Every claim in a ForIntel report traces to a public source. Findings are re-verified before delivery. The Adversary/Analyst architecture pairs a senior analyst with a counter-signal pass on every thesis. Anything below our statistical thresholds is labeled directional rather than validated.
Methodology is documented in The State of AEO and GEO in 2026 — a 9,900-word, 42-page public study with effect-size statistics across four frontier AI engines.
Ready to commission the report?
Intake takes under five minutes. We confirm scope, timeline, and cost within one business day.