Pre-commitment SaaS risk analysis

Know your integration risk before you commit

Seekora scores every SaaS tool pair on a 0-100 scale across seven risk dimensions, then automatically suggests middleware repairs when integrations fall short.

Deterministic scoringNo black-box AIExplainable penalties

Integration Score

Stripe → HubSpot

Safe
82/ 100
Depth
-5
Sync Quality
-3
Scalability
-0
Reliability
-0
Cost
-5
Data Integrity
-5
Confidence
-0
Total penalty: -18 · Score: 82/100

7 Risk Dimensions

Fully Explainable

Supported tools include:StripeHubSpotSalesforceZapierShopifySlack|and more...

Your SaaS stack is a web of hidden risks

Every integration you adopt carries invisible risks: data loss, rate-limit squeezes, auth mismatches, escalating costs, and sync failures. Most teams discover these problems only after committing months of engineering effort. Seekora surfaces them instantly.

73%

of SaaS integrations hit at least one critical friction point within 6 months

4.2x

the engineering cost to fix integration issues after commitment vs. before

7

independent risk dimensions analyzed for every tool pair by Seekora

How it works

Three steps to integration confidence

Select any two SaaS tools. Seekora scores the integration, explains every penalty, and suggests repairs.

01

Pick your tools

Select any source and target tool from our database. Seekora checks for documented integrations first, then infers compatibility using Tool DNA profiles.

02

Get your score

Receive a 0-100 Integration Confidence Score with a transparent penalty breakdown across seven risk dimensions. Every deduction is explained.

03

Repair if needed

If the score falls below the safety threshold, Seekora's Repair Engine recommends middleware tools that resolve specific clash types and improve the score.

The Engine Stack

Three engines, one verdict

Seekora's scoring pipeline combines documented data, inferred compatibility, and automated repair into a single actionable result.

ICS

Integration Confidence Score

Deterministic, penalty-based scoring. Starts at 100 and deducts points across integration depth, sync quality, scalability, reliability, cost, data integrity, and confidence level. Produces Safe, Conditional, or Risky verdicts.

IIE

Integration Inference Engine

When no documented integration exists, IIE infers compatibility from Tool DNA. Runs functional gates, object clash analysis, and DNA clash detection to produce a realistic score capped at 85.

IRE

Integration Repair Engine

When a direct A-to-B score falls below 70 or has critical risk flags, IRE tests middleware candidates (Zapier, Make, n8n, etc.), ranks them by repairability, and shows the best integration path.

Tool AICS / IIEIREVerdict + ScoreTool B

Features

Everything you need to de-risk your stack

7-Dimension Risk Scoring

Evaluate integration depth, sync quality, scalability, reliability, cost, data integrity, and confidence level in one score.

Instant Inference

No documented integration? IIE uses Tool DNA profiles - API protocols, auth types, data formats - to infer a realistic score.

Automatic Repair Paths

IRE identifies middleware tools that resolve specific clash types like protocol gaps, auth mismatches, and rate-limit squeezes.

Tool DNA Profiling

Every tool is profiled with outbound/inbound mechanisms, data formats, auth requirements, rate limits, and API access plans.

Clash Type Detection

Automatically detect protocol gaps, push/pull mismatches, auth conflicts, object clashes, and rate-limit squeezes between tools.

Transparent Penalties

Every point deducted is explained. No black-box models. See exactly which risk dimension drives the score and by how much.

Repair Engine

When integrations fall short, Seekora finds the fix

The Integration Repair Engine identifies the specific clash types causing a low score, then tests every compatible middleware tool to find the optimal repair path. Each alternative is ranked by capability match, operational friction, cost fit, and resulting score.

  • Protocol Gap

    Webhook-to-polling mismatches resolved with poller proxies

  • Auth Mismatch

    OAuth vs API-key conflicts bridged with token storage

  • Rate Limit Squeeze

    Burst-limited APIs buffered with queue middleware

  • Object Clash

    Incompatible data models mapped through transformation engines

Direct Integration

Shopify → Salesforce

48

Risky
protocol gapauth mismatchobject clash
Repair via Make (Integromat)

Repaired Integration

Shopify → Make → Salesforce

76

Conditional
protocol gap repaired
auth mismatch repaired
object clash repaired

Score improved by +28 points · Complexity tax: -5 · New risks: additional latency, single point of failure

Verdict System

Clear, actionable verdicts

Every score maps to a verdict that tells you exactly what to do next.

Safe

80-100

Go ahead with confidence. Integration is production-ready.

Conditional

60-79

Proceed with caution. Review specific risk areas flagged.

Risky

50-59

Significant risks detected. Middleware repair recommended.

Not Recommended

0-49

Critical issues found. Consider alternative tool pairings.

Stop guessing. Start scoring.

Know the real risk of every SaaS integration before you wire a single webhook. Seekora gives you the clarity your team needs to build a reliable, scalable stack.