Logistics
15 columns
121 rows
8 formats

Supplier AI Risk Assessment Logs

This dataset provides detailed, AI-driven risk assessment logs for e-commerce suppliers, including risk scores, compliance flags, disruption probabilities, and actionable recommendations. It enables operations managers to proactively identify and mitigate supplier risks, ensuring supply chain resilience and regulatory compliance. The dataset supports advanced analytics, supplier monitoring, and procurement optimization.

last updated 22 Jan 2026
by GoMask

The brief that made it

Supplier risk monitoring and early warning systems

Sample rows

preview · 8 of 121 rows · all 15 columns

log_idstring	risk_levelstring	risk_scorefloat	compliance_flagboolean	supplier_industrystring	assessment_datetimedatetime	supplier_idstring	supplier_namestring	supplier_countrystring	risk_factorsstring	disruption_probabilityfloat	last_audit_datedate	audit_scorefloat	recommendationstring	notesstring
A1B2C3D4-20240601	low	0.13	false	Transportation	2024-06-01T10:15:23Z	SUP-1001	Global Logistics Ltd.	Germany	seasonal fluctuation	0.09	2024-04-23	0.92	continue partnership	Consistently meets delivery targets.
F9G8H7J6-20240602	medium	0.67	true	Chemicals	2024-06-02T13:42:09Z	SUP-1014	EcoChem Industries	Poland	new regulations	0.45	2024-05-11	0.65	monitor	Pending environmental certification.
K2L3M4N5-20240603	high	0.84	true	Manufacturing	2024-06-03T08:27:34Z	SUP-1007	Pacific Steelworks	South Korea	labor dispute,price volatility	0.78	2024-05-19	0.55	replace	Recent strike impacted production.
O6P7Q8R9-20240604	low	0.23	false	Medical Devices	2024-06-04T16:19:11Z	SUP-1022	Meditech Solutions	USA	blank	0.13	2024-04-15	0.98	continue partnership	High audit score, low risk.
S1T2U3V4-20240605	medium	0.74	false	Food Processing	2024-06-05T12:03:56Z	SUP-1013	Tradex Foods	Norway	seasonal shortage	0.51	2024-05-06	0.81	monitor	Seasonal risks increasing.
W5X6Y7Z8-20240606	medium	0.41	false	Electronics	2024-06-06T09:30:42Z	SUP-1003	GreenTech Components	Netherlands	component shortage	0.37	2024-05-20	0.78	monitor	Supply chain affected by global shortages.
A8B7C6D5-20240607	critical	0.91	true	Textiles	2024-06-07T11:21:17Z	SUP-1020	Urban Fabrics Co.	Bangladesh	compliance violation,worker safety	0.89	2024-05-28	0.33	escalate	Critical compliance violations detected.
E4F3G2H1-20240608	low	0.17	false	Aerospace	2024-06-08T15:14:48Z	SUP-1004	AeroParts Europe	France	blank	0.15	2024-05-02	0.94	continue partnership	No significant risks detected.
I2J1K9L8-20240609	medium	0.49	false	Biotechnology	2024-06-09T07:10:24Z	SUP-1012	BioGen Labs	UK	R&D delays	0.29	2024-04-29	0.86	monitor	Minor delays in development pipeline.
M6N5O4P3-20240610	low	0.12	false	Logistics	2024-06-10T14:57:39Z	SUP-1021	FastFreight Asia	Singapore	blank	0.08	2024-04-10	0.97	continue partnership	Reliable logistics provider.
Q2R1S9T8-20240611	medium	0.38	false	Plastics	2024-06-11T12:31:15Z	SUP-1005	EuroPlastics GmbH	Austria	price volatility	0.26	2024-03-31	0.74	monitor	Price fluctuations noted.
U8V7W6X5-20240612	medium	0.6	false	Paper	2024-06-12T09:01:05Z	SUP-1019	Nordic Paper AB	Sweden	resource shortage	0.41	2024-05-18	0.77	monitor	Resource supply issues monitored.
Y4Z3A2B1-20240613	high	0.79	true	Mining	2024-06-13T16:45:37Z	SUP-1009	Eastern Minerals	China	regulatory change,geopolitical risk	0.69	2024-05-24	0.59	investigate	High regulatory risk.
C9D8E7F6-20240614	low	0.08	false	Renewable Energy	2024-06-14T11:59:32Z	SUP-1023	SolarGen Technologies	Spain	blank	0.04	2024-04-25	0.99	continue partnership	Excellent audit record.
G2H1I9J8-20240615	medium	0.58	false	Forestry	2024-06-15T13:28:54Z	SUP-1017	Westland Timber	Finland	weather risk	0.38	2024-04-19	0.81	monitor	Weather-related supply risk.
K8L7M6N5-20240616	high	0.85	true	Textiles	2024-06-16T17:36:11Z	SUP-1015	UrbanTextile SA	Turkey	worker unrest,compliance violation	0.83	2024-05-29	0.4	replace	Serious compliance issues noted.
O2P1Q9R8-20240617	medium	0.73	false	Electronics	2024-06-17T10:10:44Z	SUP-1024	Metro Electronics	India	component shortage,price volatility	0.47	2024-05-14	0.73	monitor	Component shortages remain a risk.
S6T5U4V3-20240618	low	0.25	false	Dairy	2024-06-18T08:01:27Z	SUP-1008	Alpine Dairy AG	Switzerland	blank	0.17	2024-05-03	0.95	continue partnership	Stable supply conditions.
W2X1Y9Z8-20240619	medium	0.45	true	Pharmaceuticals	2024-06-19T14:12:05Z	SUP-1025	Delta Pharma Ltd.	Ireland	regulatory delay	0.34	2024-05-11	0.66	investigate	Regulatory review outstanding.
A5B4C3D2-20240620	low	0.21	false	Logistics	2024-06-20T07:42:38Z	SUP-1011	Atlantic Shipping	Denmark	blank	0.12	2024-04-17	0.96	continue partnership	No compliance issues found.

What the 121 rows show

from the 121-row sample

High (risk level) stands out: 21 of its 21 rows have compliance_flag = true, against 9 of 100 for the rest.

25%compliance_flag = true
0.41median risk_score
5recommendations
0.29median disruption_probability
0.80median audit_score

Compliance flag rate by risk_levelcompliance_flag = true

High (risk level)'s mean risk_score is 0.75, against 0.19 for low, 0.47 for medium and 0.89 for critical.

risk_score121 rows, in bands of 0.1

Median 0.41, from 0.08 to 0.93.

supplier_industry121 rows · top 10 of 37 values

Electronics9
Textiles9
Agriculture9
Chemicals8
Logistics8
Manufacturing7
Food & Beverage6
Plastics5
Pharmaceuticals5
Paper4

15 columns by typefrom the column list below

string 9
float 3
date 1
datetime 1
boolean 1

Columns

15 columns in four groups

blueprint · 15 columns
column	type	description	example
Text 9 columns
`log_id`	string	Unique identifier for each AI risk assessment log entry.unique	A1B2C3D4-20240601
`supplier_id`	string	Unique identifier for the supplier being assessed.	SUP-1001
`supplier_name`	string	Official name of the supplier.	Global Logistics Ltd.
`supplier_country`	string	Country where the supplier is headquartered.	Germany
`supplier_industry`	string	Primary industry or sector of the supplier.optional	Transportation
`risk_level`	string	Categorical risk level assigned by the AI model.low · medium · high · critical	low
`risk_factors`	string	Comma-separated list of key risk factors identified (e.g., 'delivery delays,financial instability').optional	seasonal fluctuation
`recommendation`	string	AI-generated recommendation for action (e.g., 'monitor', 'replace', 'continue partnership').5 values	continue partnership
`notes`	string	Additional notes or comments from the AI system or human reviewer.optional	High regulatory risk.
Numbers 3 columns
`risk_score`	float	AI-generated risk score for the supplier (0.0 = low risk, 1.0 = high risk).0 to 1	0.13
`disruption_probability`	float	Predicted probability (0.0-1.0) of a supply disruption in the next 6 months.0 to 1 · optional	0.09
`audit_score`	float	Score from the last supplier audit (0.0 = poor, 1.0 = excellent).0 to 1 · optional	0.92
Dates and times 2 columns
`assessment_datetime`	datetime	Timestamp when the AI risk assessment was performed.	2024-06-01T10:15:23Z
`last_audit_date`	date	Date of the supplier's most recent compliance or quality audit.optional	2024-04-23
True or false 1 column
`compliance_flag`	boolean	Indicates if the supplier is flagged for compliance issues (true = flagged, false = clear).	false

Use it for

A logistics dashboard
The compliance_flag rate, risk_score by risk_level and a breakdown of supplier_industry. Excel, Power BI or Tableau.
Why do 30 of 121 rows have compliance_flag = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Logs121
A1B2C3D4-202406010.13low
F9G8H7J6-202406020.67medium
K2L3M4N5-202406030.84high
A software demo
Believable logs with assessment_datetime, supplier_id and supplier_name to fill a screen in front of a buyer.

This dataset121 rows15 columns

Yours1,000 rows15 columnssupplier_country: UK only

blueprint · supplier-ai-risk-assessment-logs

Behind this dataset

Same schema. As many rows as you need.

These 121 rows came out of a blueprint — 15 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Each supplier receives an AI risk score updated monthly
Scores factor in delivery delays, ESG compliance, financial health, and recent incident reports
Suppliers flagged with high risk require a review and contingency actions
Include indicators for compliance status, risk category, and escalation triggers
Data must comply with GDPR and privacy regulations

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: supplier-ai-risk-assessment-logs

What should your data show?

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Sample rows

What the 121 rows show

Columns

Use it for

A logistics dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Logistics

What should your data show?