3-Layer Evidence Collection Methodology
Traditional firms are increasingly sophisticated. The gap Signalomix solves: outputs often aren't normalized into a portfolio-grade operating system you can compare across deals, track post-close, and run as an execution agenda. We collect evidence on systems + processes + behaviors, score 420 signals against the same framework, and deliver IC scorecard + fix-first plan, diligence that becomes a management system.
Evidence → Normalization → Execution
Signalomix Technical Risk Intelligence™ is built for the problem even sophisticated firms face: diligence that's good but not operationalized into a system you can compare across deals, track post-close, and run as an execution agenda. We collect evidence across three layers (systems, processes, behaviors), score 420 signals using the same framework every time, and deliver IC scorecard + 30/60/90 operating priorities.
Result: diligence that becomes a management system, comparable, trackable, executable. Not "more consulting." A clearer decision, cleaner terms, tighter Day-1 plan, measurable path to value creation.
Three-Layer Evidence Collection
We measure 420 signals across systems (what exists), processes (how work should run), and behaviors (how work actually runs under pressure). Interviews + artifact review + exception pattern analysis across AI & Data Readiness (113 signals), Engineering Health (93), Technology Operations (108), and Cybersecurity (108).
Systems (What Exists)
Architecture, SDLC, security controls, data foundations, ML platform readiness, infrastructure scalability, reliability practices, tooling stack.
Processes (How Work Should Run)
Change management, incident response, release governance, QA gates, planning cadence, vendor management, data governance frameworks, model validation procedures.
Behaviors (How Work Actually Runs)
Decision rights in practice, leadership alignment, escalation habits, cross-functional trust, exception handling, shadow processes, follow-through when it's inconvenient. Can teams say "no" safely? Does governance have teeth under pressure?
Why three layers matter:
Technology failures show up in code, but root causes are human: unclear decision rights, weak accountability, incentives that reward speed over truth. Traditional firms note these risks; Signalomix scores them as measurable signals.
Signal Scoring & Portfolio-Grade Normalization
420 signals measured using the same framework, evidence standards, and scoring methodology every time. Benchmarked against industry cohorts (SaaS, FinTech, HealthTech, etc.) and our 50+ engagement portfolio data.
Same Framework = Comparable
Your IC can compare technical risk indices across deals, not one-off narratives. "This target scores 58th percentile for Series B SaaS engineering health" means more than "some tech debt."
Same Evidence Standards = Auditable
Every signal is evidenced the same way: artifact review + interview confirmation + exception pattern analysis. Repeatable, not subjective.
Same Scoring = Trackable
You can re-run the same 420 signals quarterly to track post-close progress, catch drift early, manage technical health as an operating view across your portfolio.
Data science techniques embedded:
This is what makes Signalomix outputs portfolio-grade: not one-off consulting, but a repeatable operating system.
Deliverable Generation: IC Scorecard + Execution Agenda
You receive an IC-ready scorecard (risk index, top 5 drivers, deal impact) + fix-first plan structured as an operating agenda (30/60/90 priorities, ownership, success metrics). Six stakeholder views: right detail for right audience.
Deal Partner 2-Pager
Kill switches, risk index, top drivers: what changes the deal model.
Operating Partner Deep Dive
Remediation roadmap, mitigation cost/timeline, execution owners.
IC Presentation
Thesis translation: tech risk → deal implications, quantified dollars at risk.
Management Heat Map
Dimension-level scoring for target company leadership.
Board Dashboard
Portfolio-grade format: track post-close, compare across deals.
Post-Close 100-Day Plan
30/60/90 priorities, ownership, metrics so diligence becomes execution.
Not "more consulting":
Diligence that becomes a management system: clearer decision, cleaner terms, tighter Day-1 plan, measurable path to value creation.
How We Measure Behavioral Evidence
If teams can't tell truth upward, can't make fast decisions, can't enforce standards, or can't retain the right leaders, your architecture review won't save you. We make human operating risk measurable.
Decision Velocity
How fast can the team make consequential decisions? Do decisions get stuck in alignment loops? Is there clear decision authority, or does everything escalate?
Escalation Patterns
Do incident escalations work under pressure or only on paper? When things break, does the org respond fast or finger-point? Is there real accountability?
Truth-Telling Culture
Can teams communicate bad news upward safely? Do status reports reflect reality, or are they optimized for optics? Does leadership want truth or comfort?
Accountability Under Pressure
When deadlines slip or quality suffers, is there follow-through? Do post-mortems lead to change or just ritual? Are exceptions handled systematically or swept under?
We don't just ask whether a process exists, we verify whether it's followed when it's inconvenient. We don't just review artifacts, we examine the behaviors those artifacts imply: who signs off, who gets blocked, how exceptions are handled, how quickly reality reaches leadership.
Why Portfolio-Grade Normalization Matters
Even when diligence is "good," it often doesn't translate into a system you can compare across deals or track post-close. Signalomix delivers the same 420-signal framework every time, so your IC gets comparable risk indices, not one-off narratives.
Same Signals Every Time
AI & Data (113), Engineering (93), Operations (108), Security (108). Same evidence collection methods, same scoring, same benchmarks. Repeatable operating view.
Comparable Across Deals
Your IC can rank targets by technical risk index. "Target A: 72nd percentile engineering health, 45th percentile AI readiness. Target B: 58th, 81st." Data-driven portfolio decisions.
Trackable Post-Close
Re-run same signals quarterly. Track progress on fix-first plan. Catch drift early. Portfolio-wide operating view of technical health, not one-off consulting engagements.
Diligence That Becomes Your Operating Agenda
IC-ready scorecard. Fix-first plan with 30/60/90 priorities. Portfolio-grade format you can compare across deals and track post-close. <2 weeks. $45K-$65K.
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