Sharp Logica, Inc.
Engineering Tools

SaaS Due Diligence Calculator

This SaaS route keeps the same base diligence engine but emphasizes SaaS-specific risk signals that materially influence valuation and post-investment execution.

Preliminary technology risk assessment. This is directional and should be followed by full technical due diligence.

Risk score

61/100

Overall assessment

Proceed with Conditions

Proceed only with clear remediation conditions and execution tracking.

Remediation cost

$165,800 - $343,800

Remediation timeline

3-6 months

Architecture

81

Technical debt

50

Delivery health

56

Team risk

63

Security

70

Cloud efficiency

50

Roadmap realism

25

Model

Weighted risk model

20/20/15/15/15/10/5

Top findings

  • -Backup/DR restoration is not validated.
  • -Roadmap realism shows elevated risk (25/100).
  • -Technical debt shows elevated risk (50/100).
  • -Cloud and infrastructure efficiency shows elevated risk (50/100).
  • -Engineering delivery health shows elevated risk (56/100).

Architecture Fitness

Architecture shape, reliability, and recovery profile.

20% Weight

Technical Debt

Maintainability pressure from coverage, bugs, and legacy constraints.

20% Weight

Engineering Delivery Health

Release velocity and change stability indicators.

15% Weight

Team and Key-Person Risk

Team resilience, documentation, and concentration risk.

15% Weight

Security and Compliance

Control posture, testing discipline, and recovery readiness.

15% Weight

Cloud and Infrastructure Efficiency

Spend exposure and platform automation maturity.

10% Weight

Product and Roadmap Realism

Forward feasibility and claim reliability.

5% Weight

SaaS Method

How SaaS Diligence Framing Differs

Highlights multi-tenant architecture quality, isolation boundaries, and operational blast-radius risk.

Connects technical posture to SaaS economics: cloud efficiency, churn-linked reliability pressure, and SLA credibility.

Frames risk interpretation for recurring-revenue systems where uptime and scale consistency have direct commercial impact.

Use when SaaS-specific sections are needed; otherwise fall back to the core hub for generic diligence triage.

Field Setup Guide

Each field below explains what to input and how to keep assumptions consistent across reviewers.

Architecture style

Select the closest current architecture pattern. Use the current production shape, not a target future state.

Prod incidents / month

Average monthly production incidents requiring real intervention, not minor alerts.

MTTR (hours)

Mean time to recover service after incidents, measured in hours.

Horizontal scaling risk

Operational risk of scaling current workloads under growth pressure.

Test coverage (%)

Practical automated test coverage for critical business paths, not vanity coverage.

Release delays / month

How often releases are delayed due to technical blockers.

Open bugs

Active unresolved defects relevant to production stability and delivery.

Legacy systems

Count of legacy dependencies that materially constrain delivery or operations.

Deployment frequency

Current delivery cadence in production under normal operating conditions.

Lead time (days)

Average days from approved change to successful production release.

Failed deploy rate (%)

Percent of deployments that fail or require rollback or hotfix.

Hotfixes / month

Monthly emergency fixes applied after release due to instability.

Team size

Number of engineers actively responsible for the platform in scope.

Bus factor

Number of people whose loss would materially disrupt delivery continuity.

Attrition (%)

Annualized team attrition rate used as concentration and continuity signal.

Documentation maturity

How complete and operationally useful architecture and runbook documentation is.

MFA enabled

Whether multi-factor authentication is broadly enforced for critical systems.

Pen test recency

How recently formal penetration testing was completed.

SOC2 status

Current compliance maturity status used as a control signal.

Secrets management

Whether secrets handling is structured and controlled rather than ad-hoc.

Backup/DR tested

Whether backup and disaster recovery restoration has been tested, not only documented.

Cloud spend / month

Monthly cloud spend for the scoped platform, including core workloads.

IaC maturity

Maturity of infrastructure-as-code and repeatable environment management.

Monitoring maturity

Depth of observability, alert quality, and operational coverage.

Rollback maturity

Reliability and speed of rollback during failed releases.

Roadmap confidence

Confidence that roadmap commitments are technically feasible on current foundations.

Major rewrite planned

Whether a major rewrite is expected, which can indicate structural risk.

AI claims validated

Whether AI-related technical claims are validated with operating evidence.

Frequently Asked Questions

+Why keep a separate SaaS page?

SaaS diligence has distinct technical-commercial coupling (SLA, tenancy, churn, infra efficiency) that deserves dedicated interpretation.

+Is this a separate calculator model?

It uses the shared diligence scoring engine, with SaaS-specific framing in methodology and interpretation.

+Should this replace the core hub?

No. Use this when your query intent is SaaS-specific; use the hub for general technical-risk triage.

+Which SaaS fields are most tied to churn and expansion risk?

Incident frequency, MTTR, deployment failure rate, and cloud efficiency signals tend to correlate strongly with commercial pressure.

+How should we set cloud spend in multi-product SaaS platforms?

Use attributable spend for the target product scope, then document shared-platform allocation assumptions explicitly.

+Can this be used in pre-exit readiness work?

Yes. It helps surface technical-commercial risk signals that buyers commonly test in their own diligence cycles.