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Compliance, built for the AI stack

Plug Inspack into your code, your agents, or your AI assistants. One compliance layer – three ways in.

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# Send artwork, get findingsPOST /api/v1/inspector/review  objects:        [label.png]  inspector_ids:  [12, 34]→ 3 findings  claim · allergen · net quantity

Trusted by

  • Snapchat
  • Hightide
  • NextEra Energy
  • Catchmaster
  • Umami
  • Pernod Ricard
  • Jägermeister

01 / Why Inspack

Why builders choose Inspack

Label compliance, streamlined for the AI stack.

Built for label artwork

Handle any input: press-ready PDFs, AI files, PNGs, photographed packaging, or structured JSON. Parse panels (front, Supplement Facts, claims, warnings) and extract elements in one call.

Checks that know label rules

FDA Supplement Facts format, DSHEA disclaimers, structure/function vs. disease claims, allergen warnings, net quantity, serving size. Versioned rulesets update automatically when regulations change, so you never rebuild to stay compliant.

Pipeline you can compose

Call upload, list inspectors, and review as separate endpoints or chain them – whatever your workflow needs. Build once, compose differently for each use case (Supplement Facts only, brand review, full artwork audit).

02 / How to build

Three ways to build

Pick the layer that matches how you build. Or use all three.

01API

Programmatic label review

Send artwork (PDF, AI, PNG, or structured text), get parsed panels and findings back. REST endpoints with an OpenAPI spec. Rate-limited per workspace, audit-logged by default.

Read the API docs
POST /api/v1/inspector/review
curl -X POST "https://app.inspack.com/api/v1/inspector/review" \
  -H "Authorization: Bearer $INSPACK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "objects": [
      {
        "type": "image",
        "content": "https://cdn.example.com/vitd3-press.png"
      }
    ],
    "inspector_ids": [123]
  }'
02MCP

Agent-discoverable label inspection

Run our MCP server in your agent stack. Claude, Cursor, and any MCP-compatible client get a typed toolset: upload files, list inspectors, run reviews, export reports. Agents compose the pipeline however they need.

See available tools
mcp.json
{
  "mcpServers": {
    "inspack": {
      "url": "https://app.inspack.com/api/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_INSPACK_API_KEY"
      }
    }
  }
}
03Skills

Agent-ready label review skills

Give your AI assistant a reusable review workflow for supplement labels. The skills pack includes instructions for FDA labeling checks, structure/function claims, DSHEA disclaimers, Supplement Facts panels, ingredients, warnings, and review handoff.

Browse skills
inspack-label-review/
inspack-label-review/
  SKILL.md
  workflows/
    review-supplement-label.md
    check-structure-function-claims.md
    verify-dshea-disclaimer.md
  examples/
    supplement-label.pdf
    expected-findings.md
  mcp/
    inspack-tools.md

03 / Pipeline

The Extract → Review → Feedback pipeline

One label, three inspection stages. Compose them however you need.

  1. Upload artwork (PDF, AI file, photo, or structured text) and process it. Identifies all panels and elements (front panel, Supplement Facts, claims, ingredients, warnings, etc.).

  2. Call get_inspectors to list the relevant rules (FDA Supplement Facts, DSHEA disclaimer, structure/function claims, allergen warnings, etc.) or let the platform recommend them, then pass your inspector list to review. Get raw findings with location and severity.

  3. The same review call aggregates findings into a clean, human-readable summary grouped by panel, severity, or inspector. Export the Insights Report as PDF, use the JSON, or feed it directly into your design tool or Jira.

Flowchart showing doc-parse processing input documents into front panel, supplement facts, claims, ingredients, and warnings.
Flowchart showing parsed panels processed by get_inspectors to select inspectors, then inspected to produce raw findings.
Aggregated findings report

Supplements is our example here; the same Extract → Review → Feedback pipeline runs for food, cosmetics, cannabis, pharma, and chemical labels.

“Inspack makes working with influencers and UGC content faster and easier. We plug its API into our workflow to automate compliance checks, so content aligns with brand, platform and regulatory rules effortlessly.”

Julia KorostelevaStrategic Partnerships at TikTok

04 / Docs

Developer resources

Label compliance, streamlined for the AI stack.

/api

API reference

/api/v1/upload/asset/inspector/get_inspectors/inspector/review/documents/report-export
/mcp

MCP server docs

Toolsprepare_uploadget_inspectorsreviewreport_export
/skills

Skills library

inspack-supplement-labelsSupplement facts panelDSHEAstructure/function claims
status.getgen.ai

Status & changelog

Service uptime, API updates, breaking changes, and release notes.

05 / FAQ

Got questions? We’ve got answers

Have questions about our services? Explore our detailed FAQ section for in-depth answers and insights.

You create as usual — ads, landing pages, or copy. If something breaks a rule or could be improved, Inspack instantly highlights it, explains why, and suggests how to fix it. You can accept the change with one click, and the text updates automatically.

Everything from digital ads, landing pages, and packaging to influencer content and partner collateral — in text, image, and video formats.

Yes! Inspack can be trained on company-specific guidelines, brand standards, and custom rules. Clients have full access to add and manage their inspectors.

Yes, Inspack seamlessly integrates with Google Docs, Jira, Microsoft Word, CMS platforms, and other workflow tools.

Most teams are up and running within days. Full integration—like customizing reports, roles, and workflows—typically takes 2–5 weeks.

Rulesets are versioned and update automatically when a regulation changes. Our regulatory experts review each update, so your content stays aligned with current legal, regulatory, and policy requirements.

Yes! You can apply multiple compliance layers—from brand rules to regulatory policies—simultaneously.

While Inspack dramatically reduces compliance errors, human oversight is recommended for high-stakes content.

Ship label-compliant from day one

Start with the API for full control, or connect the MCP server to your agent. Get structured feedback in minutes, not weeks. Read the docs or talk to a solutions engineer.

Read the docsTalk to a solutions engineer

06 / Resources

Latest on Inspack

Exploring AI, compliance, and packaging validation practices

Read more
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