Fabric for packaging design agencies

Packaging projects have more stakeholders than any other design discipline. The brand team approves the design direction. Legal reviews the claims. Regulatory checks compliance. The printer provides specs and constraints. The distributor has display requirements. Each stakeholder provides feedback through different channels. Copy changes come via email. Legal markup comes as a PDF. Print specs come from a portal. Brand feedback comes on a call. By revision four, tracking what changed, who requested it, and what the current approved version looks like requires a forensic reconstruction.

Fabric keeps every revision, every piece of feedback, and every spec searchable across all stakeholders. When someone asks "what version are we on," the answer is instant.

Every stakeholder's feedback in one searchable place

Annotations let every stakeholder pin feedback to exact spots on the packaging design: brand direction, legal markup, regulatory flags, printer notes. Draw on dielines to mark specific areas. The feedback from each stakeholder is searchable, so "every legal comment across the project" or "what the printer flagged about the bleed area" finds the relevant notes.

Forward email feedback to email-to-note. Record stakeholder calls with AI voice notes. Everything is searchable in one project workspace. The AI assistant can summarise the current state of feedback across all stakeholders.

Regulatory and copy requirements tracked

Regulatory requirements, nutritional information, ingredient lists, and legal copy changes are searchable alongside the design. When the regulatory team sends updated copy, it's findable in the project space. When legal approves a claim, the approval is documented. Self-writing docs capture decisions from meetings and Slack, so "when was the allergen statement approved and by whom" has an answer.

Print specs connected to the design

Printer specifications, colour profiles, and material constraints are searchable alongside the design files. Forward printer emails to the project space. Upload spec sheets. When the designer needs to check the bleed requirements for a specific printer, they search rather than dig through email.

Revision history and version tracking

Every version of the packaging design lives in the project space and is searchable. "The version before the legal copy change" is findable. "What changed between round two and round three" is answerable by the AI. The revision history is a searchable record, not a series of numbered files.

Polished client sharing

Publish packaging mock-ups and proofs with password protection and link analytics. Track who's reviewed the latest version. Update the design and the link serves the current proof.

For the full agency workflow, see Fabric for agencies. For review workflows, see review and approval and design feedback.

Get started

Keep every stakeholder's feedback and every spec searchable. Try Fabric free. See pricing for teams.

FAQs

Can I track feedback from multiple stakeholders?

Yes. Annotations pin feedback from brand, legal, regulatory, and printers to exact spots on the design.

Can I search for legal or regulatory comments specifically?

Yes. AI search finds feedback by meaning. "Every legal comment" or "regulatory flags" produces the relevant set.

Can I track revisions and version history?

Yes. Every version is searchable. The AI can explain what changed between versions.

Can I search print specs?

Yes. Printer specifications, colour profiles, and material constraints are searchable alongside the design.

Are decisions documented automatically?

Yes. Self-writing docs capture decisions from meetings and Slack with context.

Can I share proofs with tracked links?

Yes. Publish with password protection and link analytics.

Can I forward feedback from email?

Yes. Forward to email-to-note. The feedback is searchable in the project space.

Can I record stakeholder calls?

Yes. AI voice notes transcribe calls into searchable text.

Is client data secure?

Yes. AES-256 encryption, CASA Tier 2 compliant. Data never used for model training.