Field Content Capture Assistant

For

Marketing leads at multi-location hospitality and trade service businesses

Solves

Head office marketing teams are too far from daily operations to capture authentic moments while employees lack time to write captions.

Delivers

Branded social media posts ready for publication

Built in

about 2 weeks of creation time, MVP in 2 days

Investment

$5,500 for the MVP, $17,500 for the full product

Run it

Inside your business, or as part of your offer to clients

For marketing leads at multi-location hospitality and trade service businesses, turn raw photos and video clips into branded social media posts and schedule them for publication.

1. Capture media via mobile device.
2. Identify objects and actions using vision models.
3. Generate on-brand caption options.
4. Format content for specific social channels.
5. Queue content for review.
6. Track engagement metrics for future suggestions.

What goes in, what comes out

The workflow

1. In
   Start with

   Raw photos and short video clips from frontline staff

2. 1

   Upload media

3. 2

   Identify scene

4. 3

   Generate captions

5. 4

   Review options

6. 5

   Approve content

7. 6

   Schedule publication

8. 7

   Analyse engagement

9. Out
   Finish with

   Branded social media posts ready for publication

AI does the heavy lifting, people stay in charge

Use multimodal models to interpret visual context and generate text in the brand voice. A human marketing lead reviews and approves the drafts before publication to ensure brand safety.

What your team sees

Key screens: Capture feed, draft review queue, approval dashboard. Use a feed view where staff upload media, a queue view for marketing leads to approve drafts, and a dashboard to track content status. Display draft, pending approval and published states. Provide a quick approve or edit option. In this product, the first view is the capture feed, followed by the draft review queue and approval dashboard.

Accounts and administration

User roles for staff and managers, content approval workflows, version history for drafts, audit logs of all uploads and approvals, and permission settings for different branches.

Integrations and data access

Social media platforms for publishing, internal employee communication apps for distribution.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   2 days

   One buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   6 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will marketing leads at multi-location hospitality and trade service businesses use it to solve "head office marketing teams are too far from daily operations to capture authentic moments while employees lack time to write captions"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Prove that the system generates on-brand captions that get approved faster than manual drafting, establishing a baseline for engagement growth.
4. Measure, then decide. Track number of posts generated per week and approval time reduction percentage. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Mobile web app with camera upload, single caption draft per upload, and a simple approval dashboard for one marketing manager. Ship to two local cafés or a small trade business with no multi-platform logic.

After the MVP. Automated multi-platform scheduling, learning algorithms for content suggestions, and integration with existing marketing calendars.

What the build depends on. Access to a multimodal AI API, a mobile development framework.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

$500 per location per month

Message to test

Empower your frontline staff to become your best brand storytellers with AI-generated social content.

Where to find buyers

Industry associations for hospitality and trade services, marketing conferences.

Lead magnet

A free pilot setup for a single location to demonstrate the workflow.

The first 30 days

1. Week 1: Build mobile upload interface and basic caption generation.
2. Week 2: Add approval workflow and brand voice training.
3. Week 3: Deploy to two pilot cafés and gather feedback.
4. Week 4: Refine brand voice accuracy and prepare for paid pilot.

Paid pilot

Prove that the system generates on-brand captions that get approved faster than manual drafting, establishing a baseline for engagement growth.

Success metrics

Number of posts generated per week, approval time reduction percentage.

Retention and expansion

Recurring monthly subscription fees based on the number of active locations.

Why clients would pick it

Building a highly accurate brand voice model that adapts to specific company nuances takes significant training data and fine-tuning.

Alternatives and positioning

Employees manually writing captions which often breaks brand guidelines, or marketing teams using generic stock photos.

Main delivery costs

Cloud processing for vision and language models, hosting and maintenance of the mobile application.

Content moderation filters to prevent inappropriate uploads, approval gatekeeping to ensure brand safety, limits on daily uploads per employee.