Snapwire

One-Third of the Engineering Team. Millions of Images Processed.

Snapwire was not a stock photo library. It was an on-demand photography marketplace where Fortune 500 brands commissioned photoshoots from professional photographers. Dell needed product photos at their Austin office. Starbucks needed lifestyle shots at a chosen location. A brand needed 200 stock images on a specific topic by Friday.

The platform matched brands with photographers, handled scheduling, managed the shoot logistics, processed and delivered images through a CDN pipeline, handled licensing, and split payments via Stripe Connect. Tens of thousands of photographers and brands on the platform. Millions of images processed.

EltexSoft provided 10 of the 30-person engineering team for 2.5 years. We were one-third of the engineering capacity.

How We Fit Into a 30-Person Team

Snapwire’s CTO was based in Toronto. The internal team was split between Canada and California. When we joined, the platform was already a few years into development with multiple modules live: order system, both sides of the marketplace, matching engine, payouts, and storage infrastructure.

We did not come in to rescue a failing project. We came in to add capacity to a well-run engineering organization that needed to move faster. The codebase was well-built. The roadmap was structured with quarterly north stars and annual planning. Sprints were specced. The work was real engineering, not guesswork.

Our 10 engineers covered backend, frontend, mobile, QA, DevOps, and project management. Our tech lead had 15 years of experience and had previously managed 90 servers on call at NOSphere Ventures. He led our side of the development.

This is the team augmentation model at its best. Not “here are some bodies.” One-third of a serious engineering organization, integrated into the same codebase, the same sprints, and the same standards.

What We Built

Image Processing and Delivery Pipeline

The platform was built around media. Everything depended on fast, reliable image handling at scale.

Photographers uploaded high-resolution raw files. The pipeline processed each upload into multiple formats: cropped previews for browsing, scaled versions for review, and full-resolution originals for final delivery. All stored on AWS S3, delivered through CDN for near-real-time access.

The challenge was not “how do you store images.” It was “how do you process millions of images into multiple formats, deliver previews instantly while the full-resolution version is still processing, and handle raw camera formats from dozens of different camera manufacturers without losing color fidelity or metadata.”

We built the cropping and image manipulation tools, the CDN storage pipelines for content delivery, and the content management interface that let brands browse, review, select, and download their commissioned photos.

Matching Engine

The algorithm that connected brands with the right photographers considered multiple signals:

Availability. Calendar integration showing when photographers were free for on-site shoots or had bandwidth for remote assignments.

Experience. Past work with similar brands, similar industries, similar shoot types. A photographer who had shot product photos for Dell was a better match for a similar enterprise product shoot than someone whose portfolio was primarily weddings.

Tags and topics. Subject matter expertise matched against brand requirements. Lifestyle, product, food, architecture, portrait, event.

Quality scores. Both photographers and brands had reputation scores based on completed assignments, delivery timeliness, and rating feedback.

Geography. For on-site shoots, proximity to the shoot location. No point matching a New York photographer for a shoot in San Diego.

AI-Powered Image Tagging and Quality Scoring

AWS machine learning services handled automated image tagging (identifying objects, scenes, and themes in uploaded photos) and quality scoring (evaluating technical quality: sharpness, exposure, composition). These automated assessments supplemented manual curation and fed back into the matching algorithm.

Search Infrastructure

Elasticsearch powered the platform’s search and discovery. Brands searched for photographers by specialty, location, availability, and past work. Photographers searched for available assignments. The search index was updated in near-real-time as new photographers registered, new assignments posted, and new portfolio images were uploaded.

Platform Restyling and Registration Wizards

We rebuilt the platform’s frontend and designed registration wizards for both sides of the marketplace. Photographer registration: portfolio upload, availability setup, payment configuration, specialty tagging, equipment listing. Brand registration: company verification, project brief templates, budget configuration, team member access. Both flows were multi-step, validated at each stage, and designed to minimize drop-off.

Payments

Stripe Connect for marketplace payment splitting. Brands paid Snapwire. Snapwire took its commission. Photographers received their payout. Per-assignment pricing, bulk project pricing, and usage-based licensing fees all handled through the same payment infrastructure.

Content Moderation

Pre-moderation for platform quality. Photographer portfolios reviewed before going live. Assignment deliverables reviewed before release to brands. Automated flagging for quality thresholds supplemented by manual review. The platform was top-tier and the moderation reflected that.

The Stack

Laravel backend. React frontend. PostgreSQL database. Elasticsearch for search and discovery. AWS S3 for image storage. AWS CloudFront CDN for delivery. AWS machine learning services for image tagging and quality scoring. Stripe Connect for marketplace payments. Advanced CI/CD pipelines with test coverage across the full stack.

The Numbers

10 EltexSoft engineers out of a 30-person engineering team.

2.5 years of continuous engagement.

Tens of thousands of photographers and brands on the platform.

Millions of images processed through the pipeline.

Fortune 500 clients including Dell and Starbucks.

Acquired by StudioNow in 2021-2022. The platform continues operating under the new brand.

What This Engagement Demonstrates

Snapwire is not a story about rescuing a failed product or building from scratch. It is a story about scaling a working engineering organization.

When a 30-person team needs to move faster, the options are: hire internally (3-6 months to find, interview, onboard, and ramp), or add a vetted external team that integrates into the existing codebase and process from week one. We were the second option, and we delivered one-third of the engineering output for 2.5 years.

The tech lead we provided had managed 90 servers on call. The engineers we staffed worked in the same sprints, the same codebase, and the same code review process as the Canadian and California teams. When the platform was acquired by StudioNow, the engineering passed due diligence.

Who We Are

EltexSoft is a boutique software engineering studio. 35-50 senior engineers. Headquartered in Lisbon, Portugal. Engineering team in Ukraine. Founded in 2015.

Snapwire is one of our largest team augmentation references. We also built HeyTutor (9-year EdTech marketplace), Nautical Commerce ($30M Series A marketplace, acquired), and a US sports operations platform (100% of NFL teams). We build with Laravel, React, PHP, Django, iOS, and Android.

5.0 Clutch rating across 30+ verified reviews. 200+ five-star Upwork reviews. Top Rated Plus and Expert-Vetted agency status (top 1%). Average client engagement: 3+ years.

30-minute technical call. Bring your scaling challenge, your image processing problem, or your marketplace architecture question. We’ll tell you what we’d build and what we wouldn’t.

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