DEV Community: Terglos

I built an open-source WhatsApp Business inbox for teams — here's how

Terglos — Fri, 27 Feb 2026 20:01:34 +0000

The problem

If you've ever tried integrating WhatsApp Business API for customer support, you know the pain: Meta's verification process, webhook configuration, message template management, media
handling, real-time updates... and then you need a UI for your team to actually use it.

The existing options are either expensive SaaS platforms or closed-source tools you can't customize. I wanted something self-hosted, open-source, and easy to deploy.

So I built Tercela.

What is Tercela?

Tercela is an open-source omnichannel platform for customer communication. Right now it supports WhatsApp — you connect your WhatsApp Business account and get a shared inbox where your team can manage all conversations.

Features

Shared inbox — all WhatsApp conversations in one place
Real-time messaging — messages appear instantly via WebSocket
Message templates — create, edit, and sync templates with Meta
Contact management — centralized contact database
Agent assignment — route conversations to team members
Media support — images, audio, video, documents via S3-compatible storage
Multi-language UI — English, Spanish, Arabic, Hindi, Indonesian, Turkish

The tech stack

I made some deliberate choices here that I'm happy with:

Layer	Technology	Why
Backend	Hono + Bun	Hono is lightweight and fast, Bun gives native performance
Frontend	Nuxt 4 + Nuxt UI	File-based routing, auto-imports, great component library
Database	PostgreSQL + Drizzle ORM	Type-safe queries, automatic migrations on boot
Real-time	Bun native WebSocket	No Socket.io overhead, pub/sub built-in
Auth	JWT (HS256)	Simple, stateless
API docs	OpenAPI + Scalar	Interactive docs auto-generated from route definitions

Monorepo structure

tercela/
├── apps/
│ ├── api/ # Hono + Bun (port 3333)
│ └── web/ # Nuxt 4 (port 3000)
├── packages/
│ └── shared/ # Shared types & utilities
└── docker-compose.yml

Architecture decisions

Channel adapter pattern

This is probably the most important design choice. Instead of hardcoding WhatsApp everywhere, I built an adapter interface. WhatsApp is just one implementation.

Adding a new channel (email, webchat, Telegram) means implementing that interface — the inbox, contacts, and routing all work the same regardless of the channel.

Drizzle ORM with named schemas

Instead of dumping everything in the public schema, I organized tables into PostgreSQL schemas:

auth → users
channels → channels, templates
contacts → contacts
inbox → conversations, messages
config → settings
storage → media

This keeps things clean as the database grows.

Bun native WebSocket

No Socket.io, no ws package. Bun has built-in WebSocket support with pub/sub. When a new message comes in via webhook, the API publishes to the relevant topic and every connected client gets
the update instantly.

Auto-migrations on boot

Drizzle migrations run automatically when the API starts. No manual db:migrate step in production — deploy and it just works.

What's next

AI / Chatbot support
Webchat widget (embed on any website)
Email channel
Analytics dashboard

Looking for feedback

This is early stage and I'd love to hear from the community:

Does this solve a real problem for you?
What channels would you want to see next?
Architecture feedback — what would you do differently?

Contributions are welcome — even if it's just opening an issue with a feature idea.

tags-dev / tercela

Open-source omnichannel platform for customer communication

Tercela

Open-source omnichannel platform for customer communication

Connect channels like WhatsApp, manage conversations in real time, and organize contacts — all in a unified interface.

Features · Quick Start · API Docs · Contributing · Roadmap

Features

Messaging

Omnichannel inbox — Manage all conversations from a single dashboard
WhatsApp integration — Send and receive messages via WhatsApp Cloud API
Real-time updates — WebSocket-powered live messaging
Message templates — Create, edit and sync WhatsApp message templates with Meta
Media support — S3-compatible storage for images, audio, video and documents

Management

Contact management — Centralized contact database with metadata
Agent assignment — Route conversations to team members
Channel adapter pattern — Extensible architecture to add new channels

Developer Experience

REST API with OpenAPI docs — Interactive API reference via Scalar
Automatic migrations — Versioned database migrations applied on boot
Docker-ready — One command to run the entire stack
Monorepo — Clean separation…

View on GitHub

We Built an AI Fashion Photography Platform - Real Feedback Needed from Industry Professionals

Terglos — Mon, 20 Oct 2025 17:21:00 +0000

We Built an AI Fashion Photography Platform - Real Feedback Needed from Industry Professionals

Hey folks,

My team has been working on bercela.com for a while now, and before we go all-in on scaling this AI fashion photography platform, I want to hear from actual designers, brand owners, and e-commerce managers - not just our echo chamber.
What Bercela Does: AI-Powered Fashion Content Creation
Bercela is an AI model generator and virtual try-on platform designed specifically for fashion brands and creators. Here's what you can do with it:

Core Features
1. Virtual Try-On Technology
Upload photos of your clothing pieces and our AI models wear them with photorealistic precision. Whether you're working with flat lay product photos or existing model shots, the AI handles virtual clothing changes in seconds.

2. AI Fashion Models
Access virtual models without the cost of traditional photoshoots. Our AI-generated fashion models provide diversity in representation - different body types, ethnicities, ages, and styles - all without hiring physical models or booking studio time.

3. Intelligent Accessory Placement
This is where things get interesting. Our AI doesn't just swap clothes - it naturally positions accessories like jewelry, glasses, bags, scarves, and shoes on models. The system understands how accessories should sit on the body, creating realistic fashion imagery that looks professionally styled.

4. Background & Scene Changes
Transport your models anywhere. Change studio backgrounds, create outdoor scenes, or match your brand's specific aesthetic. All processed in approximately 30 seconds per image.

5. Complete Lookbook Generation
Create entire fashion catalogs and lookbooks in minutes instead of days. Upload your collection, select your AI models, customize backgrounds, and generate hundreds of professional images ready for e-commerce, social media, marketing campaigns, and print catalogs.
Current Traction & Market Validation
5,000+ fashion professionals are currently using Bercela, which gives us some validation but we need to dig deeper. Here's what early users report:

70% reduction in visual content production time
Catalog creation compressed from weeks to days
Cost savings on traditional photoshoots (no model fees, no studio rental, no photographer rates)
Fast iteration: Test multiple looks, models, and backgrounds without reshooting

Processing time: ~30 seconds per image.
The Competitive Landscape: AI Fashion Photography in 2025
We're not the only ones in this space. Competitors like Botika, FASHN.AI, Pic Copilot, and CreatorKit are all tackling AI-generated fashion imagery. Here's what we see:
Market Trends

Botika focuses on AI-generated models with their own foundation models trained on fashion data
FASHN emphasizes virtual try-on API integration for existing apps
Pic Copilot targets DTC brands and marketplaces with multicultural AI fashion avatars
CreatorKit offers unlimited generations with drag-and-drop editors

Where Bercela Differentiates

Accessory intelligence: Natural placement of jewelry, bags, glasses - not just clothing swaps
30-second processing: Faster turnaround than many competitors (some take 15+ minutes)
Complete lookbook workflows: End-to-end catalog creation, not just individual images
5,000+ active users: Proven traction in the fashion professional market

But here's the thing - we need to know if we're actually solving real problems or just building cool tech.
The Critical Questions I Need Answered
This is where I need brutal honesty from designers, brand owners, e-commerce managers, and fashion marketers:

Market Acceptance of AI Fashion Content Is AI-generated fashion imagery actually acceptable in your market? I know consumers are getting more savvy about AI content. Some brands embrace it, others hide it. Where do you stand?

Do your clients/customers care if models are AI-generated?
Does it matter for e-commerce vs. editorial vs. social media?
Are there specific fashion categories where AI works better or worse? (luxury vs. fast fashion, accessories vs. full outfits, etc.)

Quality Threshold for Trust What specific quality markers would make you trust this for your business? Be specific. Is it about:

Fabric texture realism?
Lighting consistency?
Body proportions and fit accuracy?
Shadow and reflection details?
Skin tone and makeup naturalness?
Accessory positioning precision?

What would make you look at an AI-generated image and say "yes, this is good enough for my brand"?

Deal-Breakers & Failure Points If you tried Bercela (or any AI fashion tool) and it sucked, what specifically would make you bounce? I want to know the specific failures that would make you quit:

Unrealistic fabric draping?
Weird hands or facial features?
Poor color accuracy?
Inconsistent lighting?
Can't match your brand aesthetic?
Processing too slow?
Limited model diversity?
Bad accessory placement?

Tell me what would break your trust so we can fix it before scaling.

Pricing & Value Proposition Ballpark - what's this worth monthly to a small/medium fashion brand? Traditional photoshoot costs vary wildly:

Local photographer + model: $500-2,000 per shoot
Professional studio session: $2,000-10,000+
Full catalog production: $10,000-50,000+

Given that AI fashion tools can generate hundreds of images for a fraction of that cost, what's fair pricing?

$50/month for small brands?
$200/month for medium brands?
$500/month for agencies?
Pay-per-image credits?
Unlimited generation subscriptions?

I need real numbers from people actually spending money on fashion content.
Why This Feedback Matters: The AI Fashion Photography Market
The AI fashion model industry is exploding. Here's why your feedback could shape how this technology evolves:
Industry Pain Points We're Targeting

Cost Reduction
Traditional fashion photography is expensive. AI fashion generators can cut costs by 70-90% while maintaining professional quality.
Speed to Market
Fashion moves fast. Waiting weeks for photoshoots delays product launches. AI-generated fashion content enables same-day catalog updates.
Diversity & Representation
Brands want diverse models but hiring multiple models multiplies costs. AI model portfolios offer unlimited diversity without additional expense.
Testing & Iteration
Try different looks, backgrounds, and styling without reshooting. A/B test imagery before committing to expensive production.
Sustainability
Reduce the carbon footprint of physical photoshoots - no travel, no studio waste, no overnight shipping of samples.
The Technology Behind AI Fashion Models
Without getting too technical, here's what makes modern AI fashion photography work:

Generative AI models trained on millions of fashion images
Computer vision understanding fabric physics, body proportions, and lighting
Virtual try-on algorithms that map clothing onto different body types
Style transfer technology for consistent brand aesthetics
Accessory positioning AI that understands how jewelry, bags, and accessories naturally sit on the body

Bercela processes all this in ~30 seconds per image, which is significantly faster than many competitors.
Comparing AI Fashion Photography Solutions
Here's how Bercela stacks up against traditional methods and competitors:
Traditional Fashion Photography

Pros: Maximum creative control, unique imagery, brand-specific
Cons: Expensive ($2k-50k+ per shoot), slow (weeks of planning + shooting + editing), inflexible (reshoots cost more)

AI Fashion Platforms (Bercela, Botika, FASHN, etc.)

Pros: Fast (minutes), affordable (fraction of photoshoot costs), flexible (unlimited iterations), scalable (hundreds of images quickly)
Cons: Less unique (AI models used by multiple brands), quality still improving, consumer perception questions

The Hybrid Approach
Many brands are using both: traditional photography for hero images and brand campaigns, AI-generated content for catalog bulk and social media volume.
Is this the right strategy? I want to know what you think.
Use Cases: Who Should Use AI Fashion Photography?
Based on our 5,000+ users, here's who benefits most:
E-commerce Fashion Brands

Shopify stores needing constant product imagery
Amazon sellers wanting multiple lifestyle shots per SKU
DTC brands launching new collections monthly

Fashion Designers & Small Labels

Independent designers who can't afford model shoots
Emerging brands building their first catalogs
Sustainable fashion brands reducing production waste

Marketing Agencies & Content Creators

Agencies managing multiple fashion clients
Social media managers needing daily content
Fashion influencers creating styled looks

Fashion Marketplaces & Retailers

Multi-brand platforms standardizing product imagery
Vintage/resale platforms enhancing product photos
Dropshipping businesses without original photography

Does your business fit any of these? What am I missing?
The Honest Reality Check
Here's what I'm worried about:

Quality perception: Are AI models "good enough" or do they still look uncanny?
Market saturation: If everyone uses AI models, does fashion imagery become generic?
Consumer trust: Will shoppers lose confidence if they know models are AI?
Technical limitations: What fashion categories does AI still struggle with?
Pricing sustainability: What can small brands actually afford vs. what development costs require?

I'd Rather Hear "This is Trash Because X"
Seriously. Polite feedback doesn't help us improve. I need to know:

What sucks right now?
What would make you switch from traditional photography?
What would make you choose Bercela over competitors?
What features are we missing?
What's the maximum you'd pay monthly?

Try Bercela & Give Feedback
Link: bercela.com
If you're a designer, brand owner, e-commerce manager, or fashion marketer, I want your honest take. Create a free account, test the AI fashion model generator, try the virtual try-on features, and tell me what breaks.
Keywords I'm targeting for search:

Fire away. 👊
https://bercela.com/