Data security infrastructure

Find and protect sensitive data across your cloud

slim.io connects to AWS, Azure, GCP, SaaS apps, and databases. It scans every record, detects PII, enforces your policies, and handles the rest — redact, tokenize, or encrypt.

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POST /api/v1/orchestrate — azure-blob/customer_records

Scan Audit Policy

1{ "name": "Jane Cooper", "ssn": 078-05-1120, "email": jane@acme.co }

2{ "name": "Marcus Chen", "phone": +1 (416) 555-0142, "mrn": MRN-20847 }

3{ "name": "Aisha Patel", "card": 4532 1488 0343 6467, "dx": E11.9 }

4{ "name": "Tom Rivera", "ssn": 219-09-9999, "iban": DE89 3704 0044 ... }

5{ "name": "Lin Zhou", "sin": 046-454-286, "medicare": 1EG4-TE5-MK72 }

6{ "name": "Sara Ahmed", "dl": S530-4000-0000, "rx": Lisinopril 10mg }

→ redacted output:

1{ "name": "Jane Cooper", "ssn": ***-**-****, "email": [EMAIL] }

Live intercept

Wherever your data goes, slim.io follows.

Every prompt, RAG context injection, fine-tuning export, and API call is inspected in real time. Sensitive data is caught at the boundary — before it reaches the model or leaves your control.

INTERCEPTING api.slim.io / v1 / intercept

3,841 requests/hr 247 entities caught avg 8ms

Time

Source

Type

Action

Entity Map

Waiting for intercept…

framework

policy

action

latency

Connectors

Scan where your data already lives

Point slim.io at cloud storage, SaaS apps, or databases. One config. No agents to install.

☁

Azure Blob

AWS S3

Google Cloud

✉

OneDrive

SharePoint

Salesforce

▱

Slack

Google Drive

PostgreSQL

MySQL

❄

Snowflake

Oracle

SQL Server

DB2

📁

NAS / SMB

+ custom via API

Detection

Context-aware PII detection across 6 industries

Not just regex. slim.io uses pattern matching, Luhn validation, BIN range checks, and contextual keyword scoring to minimize false positives.

Identity & Finance

SSN

SIN

Visa ✓

Amex ✓

Phone

IBAN

SWIFT

Healthcare & Government

MRN

ICD-10

Medicare

EIN

Clearance

Case #

Education & Retail

Student ID

GPA

Order #

Loyalty ID

40+ entity types

Healthcare (MRN, ICD-10, prescriptions), finance (credit cards, IBAN, SWIFT, FICO), government (EIN, case numbers, clearances), education (student IDs, GPA, transcripts), and retail (order numbers, loyalty IDs). Each with industry-specific validation rules.

View full entity catalog

Detected entityScore

SSN 078-05-11200.95

base 0.80 + 0.15 context: "social security number"

Visa 4532-1488-...0.92

base 0.90 ✓ Luhn ✓ BIN range

123-45-67890.42

base 0.80 - 0.30 context: "product code" ✗ skipped

Context-aware confidence scoring

Base confidence per entity type, boosted or penalized by surrounding keywords. SSN near "social security" scores 0.95. The same pattern near "product code" drops to 0.42 and gets skipped. Threshold: 0.6 minimum to flag.

How scoring works

Input: 078-05-1120

mask ***-**-****

hash sha256:a3f2c8...

category [SSN]

partial ***-**-1120

Five redaction strategies

Mask with asterisks, SHA-256 hash for reversible lookups, category replacement ([SSN], [EMAIL]), partial masking that preserves last-four, or full removal. Choose per entity type, per policy.

Redaction reference

Policies

Governance rules as code

Define what to detect and how to handle it. Policies evaluate against scan results and produce PASS, WARN, or FAIL.

policy.yaml

framework: hipaa rules: - rule_id: R1 name: "No unredacted PHI" metric: high_risk_count operator: ">" value: 0 severity: CRITICAL - rule_id: R2 name: "Warn on medium risk" metric: medium_risk_count operator: ">" value: 5 severity: MEDIUM scope_provider: azure

Evaluation result

No unredacted PHI

high_risk_count > 0 · CRITICAL

PASS

Warn on medium risk

medium_risk_count > 5 · MEDIUM · azure

WARN (8)

status: WARN
violations: 1
action: redact + alert

Architecture

How slim.io processes your data

Connector
Azure, S3, PG...

→

Stream
chunked, UTF-8

→

PII Detect
40+ entities

→

Risk Score
aggregate

→

Policy
PASS / WARN / FAIL

→

Action
redact, tokenize, alert

Streaming
Chunk-based with 100-char overlap. No full-file buffering. Backpressure-aware.

Distributed locking
TTL-based locks prevent duplicate scans. 60s lease, auto-renewal on iteration.

Deduplication
Cross-chunk dedup via index tracking. Same entity found in overlapping chunks is counted once.

Why slim.io

Built for AI pipelines, not email scanning

slim.io

Legacy DLP

Streaming scan (no full-file buffer)

Yes

Context-aware confidence scoring

Yes

Policy-as-code (YAML)

Yes

Industry-specific entities (ICD-10, MRN, FICO)

Yes

Partial

Luhn, BIN, and format validation

Yes

14+ native connectors

Yes

3-5

Compliance

Six compliance frameworks. Built into the policy engine.

HIPAA

PHI detection across MRN, ICD-10, prescriptions, lab results. Built-in policy rules for HIPAA-scoped data handling.

GDPR

PII detection with hash-based redaction for right-to-erasure workflows. Policy rules scoped to EU data residency.

PCI-DSS

Credit card detection with Luhn validation and BIN range matching. Visa, Mastercard, Amex, Discover, Diners, JCB.

SOC 2

Control mapping engine with audit logging of every scan, detection, and policy evaluation. SOC 2 control tracking built-in.

FISMA

Government entity detection. Case numbers, security clearances, permit IDs, tax IDs (EIN/TIN). Scoped policy rules.

FERPA

Education records detection. Student IDs, GPA, transcript IDs, course codes. Scoped policy rules per institution.