Inline AI data security · real-time · zero-trust

Stop sensitive data before it reaches your models.

Every prompt. Every RAG context. Every fine-tuning export. slim.io intercepts PHI, PII, and financial data in under 100ms, before it ever touches a model. One line to integrate. Zero workflow changes.

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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] }

The blind spot

Legacy DLP was built to scan files at rest, not intercept live AI traffic. As your team feeds customer records, medical data, and financial information into LLMs, traditional tools are watching the wrong pipe.

5–25%Accuracy of legacy DLP on unstructured AI prompts

100%of live AI requests that bypass file-scanning tools entirely

<100msslim.io inline intercept latency, invisible to your users

01 / 05The Question

00:00

Every Second,

Your Sensitive Data

Flows Into AI.

02 / 05The Risk

00:08

Three Destinations

Your Data Is Already Moving.

Large Language Models

OpenAI · Anthropic · Google

Every prompt, every RAG chunk, every fine-tune export leaves your perimeter.

At Risk

PIIPHICredit CardsSource Code

Agentic AI

Tool Calls · Autonomous Agents · MCP

Agents read your databases, call your APIs, and pass raw data across tool boundaries.

At Risk

API KeysDatabase RowsCustomer Records

III

Cloud & On-Prem Stores

S3 · Azure · GCP · Postgres · Oracle

Years of accumulated files, logs, and tables — most of it unclassified, all of it indexable.

At Risk

Medical RecordsContractsBackups

03 / 05The Solution

00:20

The Instrument

One Line Between Your Data And Every Model.

Source

Your Cloud & On-Prem

S3 · Azure · GCP · Postgres · Oracle

The Instrument

slimio

Inline · <100ms

Destination

Models & Agents

OpenAI · Anthropic · Google

Personal Information

Names, Emails, Phones, Addresses

Scanning

Payment Data

Credit Cards, Bank Accounts, IBAN

Scanning

Health Records

Medical Numbers, Diagnoses, Prescriptions

Scanning

Credentials

API Keys, Tokens, Passwords

Scanning

Identifiers

Passports, SSN, Driver Licenses

Scanning

04 / 05The Console

00:33

One Unified Console

See Every Sensitive Byte In Motion.

console.slim.io / Live

Live · 47 Connections

Scans This Hour

Entities Protected

Median Latency

0.0 ms

Models Governed

Timestamp
Source
Entity
Action
Count

12:04:31.882
api-gateway
Credit Card
● Tokenized
4

12:04:31.991
rag-index
Medical Record
● Redacted
1

12:04:32.104
claude-agent
API Key
● Blocked
2

12:04:32.218
postgres-logs
Email Address
● Masked
17

12:04:32.330
openai-proxy
SSN
● Redacted
3

12:04:32.447
s3-prod-backup
Phone Number
● Masked
9

12:04:32.561
salesforce-bot
IBAN
● Tokenized
1

12:04:32.680
internal-wiki
Passport
● Blocked
1

Active Policies

HIPAA PHI Protection

● Enforced

PCI-DSS Tokenization

● Enforced

LLM Prompt Redaction

● Enforced

Agent Tool Call Filter

● Enforced

Cross-Border Data Block

● Enforced

05 / 05The Close

00:38

slimio

Sensitive Data. Always Protected.

Book a demo→

slim.io / demo

0:00

Click to play · 56s

Live intercept

Wherever your data goes, slimio 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 <100ms

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

Microsoft Teams

Databricks

BigQuery

+ 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

19 entity types · 170+ detection rules

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

Scoring + LLM Assist

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. An optional LLM Assist pass then removes false positives before any action fires. Opt-in, tokenized before leaving your infra.

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

Architecture

From data to decision in under 100ms.

Every record passes through slim.io's intercept layer: classified, scored, and enforced in real time.

slim.io — live intercept pipeline

LIVE

PostgreSQL

prod-cluster

Snowflake

data-warehouse

AWS S3

3 buckets

BigQuery

data-warehouse

slim.io intercept

<100ms avg · 170 rules

SSN

97% conf · 12.8k today

Credit Card

Luhn · 34.3k today

PHI

HIPAA · 2.3k today

PII (NER)

Neural · 67.9k today

TOKENIZE

45.2k today

REDACT

8.4k today

BLOCK

1.2k today

PASS

892k today

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 slimio processes your data

Connector
Azure, S3, PG...

→

Stream
chunked, UTF-8

→

PII Detect
19 entity types

→

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.

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.

Stop sensitive data before it reaches your models.

Wherever your data goes, slimio follows.

Scan where your data already lives

Context-aware PII detection across 6 industries

Every request. One layer. Real time.

From data to decision in under 100ms.

Governance rules as code

How slimio processes your data

Legacy DLP scans files. slim.io intercepts requests.

Six compliance frameworks. Built into the policy engine.

Start scanning in five minutes