Serious about building? So are we...
We don’t build apps. We build systems
that move the needle.
We design software with real-world traction in mind — built to integrate, scale, and perform. Whether it’s internal tooling, automation, or customer-facing solutions, we keep it lean and purposeful. No bloated features, no vague roadmaps. Just systems that solve problems. If you’re building something serious — we’re ready when you are.
Smart Systems. Clean Execution
what can we Engineer for you?
AI-Powered Automation
We build intelligent tools that streamline workflows, eliminate repetitive tasks, and enhance operational efficiency across your team.
Custom Software Development
From concept to deployment, we create tailored applications built around real-world needs, not cookie-cutter templates.
Internal Tooling & Workflow Systems
From team utilities to asset tagging engines, we build operational infrastructure that fits your environment and evolves with your needs.
Systems Integration & Deployment
We connect your tools, platforms, and databases into a seamless system that performs reliably across your existing operations.
Explore our latest work
Showcasing 5 Projects
VideoTagger – Automating Metadata for Faster, Smarter Post-Production
VideoTagger was developed to streamline one of the most overlooked (and time-consuming) aspects of video production: metadata tagging. As enterprise teams scale their content operations, the ability to catalog, retrieve, and repurpose footage efficiently becomes a major bottleneck. VideoTagger solves this by using AI to generate high-quality metadata — automatically.
Most teams rely on default filenames, scattered folder structures, or manual logging to manage video assets. This leads to wasted time, poor discoverability, and unnecessary operational friction. For enterprises working across departments or delivering large volumes of video content, the impact on workflow and searchability is significant.
VideoTagger analyzes video content using computer vision and AI to auto-generate tags, summaries, and descriptive metadata. It works offline, requires no technical setup, and outputs structured data ready for integration into DAM systems, production databases, or cloud storage platforms. The interface is built for speed — drag-and-drop, tag, export. Simple, scalable, and fast.
Whether for internal training libraries, branded content archives, or client deliverables, VideoTagger helps teams reduce manual overhead and maintain content clarity at scale. It’s not just about tagging — it’s about creating systems that grow with your content. Enterprises use VideoTagger to increase asset visibility, improve content retrieval, and reduce time lost in post-production chaos.
PhotoTagger – AI-Driven Image Tagging for Instant Brand Organization
PhotoTagger was built to solve the content backlog that plagues internal photo libraries. For creative teams, marketing departments, and content producers, the ability to search, sort, and deploy imagery quickly is essential — yet most assets sit unlabeled, untagged, and underutilized. PhotoTagger changes that with automated, high-quality image tagging powered by AI.
Image libraries grow fast — especially in environments where photography plays a core role in branding or documentation. But without consistent, accurate metadata, those photos become hard to navigate. Traditional DAM systems still rely on manual uploads, manual tags, or file naming conventions that fall apart as volume increases. That creates content silos, redundancy, and creative inefficiency.
PhotoTagger uses computer vision and machine learning to scan images and generate meaningful, brand-relevant tags in seconds. Whether it’s identifying objects, people, settings, or branded elements, the system turns folders of raw images into organized, searchable archives. The app is lightweight, runs locally, and outputs clean, exportable metadata compatible with most digital asset platforms.
Enterprises with growing visual libraries need tools that scale without slowing down teams. PhotoTagger helps organizations unlock the full value of their photo assets by making them findable, filterable, and ready for deployment — across campaigns, departments, and use cases. It’s not just tagging — it’s metadata infrastructure for the modern brand.
AudioTagger – Turning Raw Audio into Organized, Searchable Archives
AudioTagger was created to bring structure to the most difficult asset type in digital content libraries: raw audio. Unlike images or video, audio content is notoriously harder to process, label, and sort — especially in environments where naming conventions and metadata are either missing or inconsistent. AudioTagger introduces a practical solution: semi-automated metadata tagging, built specifically for audio professionals and media teams.
AI has made impressive strides in visual recognition, but audio tagging still lags behind — especially when dealing with ambient recordings, field samples, or sound effects. Traditional audio management relies heavily on manual logging, folder structures, and naming habits that break down at scale. For studios, podcasters, or media archives, this becomes a major bottleneck when working with large audio libraries.
AudioTagger blends machine intelligence with smart, guided heuristics to generate useful metadata for sound files — without relying on full transcription or unreliable speech-to-text models. It focuses on length, dynamics, structure, and contextual cues to propose tags that are relevant and editable. The system is optimized for WAV, AIFF, FLAC, and other uncompressed formats, making it ideal for professional workflows.
For organizations managing large libraries of music cues, production audio, or sound design assets, AudioTagger fills the gap left by most DAM systems. It gives teams a way to catalog, filter, and reuse audio content quickly without wasting time on repetitive manual entry. More than just tagging — it’s a productivity layer built for audio-first teams.
GigHunter V1 – Targeted Client Discovery Through Smart Facebook Automation
GigHunter was created to solve a problem every freelancer and small agency faces: how to find consistent, qualified clients without cold pitching or wasting time scrolling through job boards. The tool leverages Facebook Groups — still one of the most active and underutilized ecosystems for lead generation — and turns them into a passive, automated discovery system.
Finding work online is time-consuming, noisy, and often full of friction. Facebook Groups are rich with real-time job opportunities, but manually scanning posts, checking for relevant keywords, and tracking leads is repetitive and inefficient. Most creators miss high-quality gigs simply because they’re not online at the right moment — or they can’t monitor enough groups at once.
GigHunter automates the process of scanning Facebook Groups for opportunities based on customizable keyword triggers. It runs in the background, detects new posts that match specified criteria, extracts metadata, and logs the information into an organized local database. It flags potential leads without spamming or interacting with content, making it safe, discreet, and effective.
Whether you’re a freelancer, consultant, or agency builder, GigHunter turns passive lurking into active opportunity capture — without wasting hours glued to the feed. It empowers users to scale outreach, identify trends, and build smarter workflows around lead generation. Built for people who want to grow without begging for attention.
GigHunter V2 – Multi-Profile Lead Intelligence for Facebook Group Prospecting
GigHunter V2 takes client discovery to the next level. While Version 1 automated the detection of keyword-based posts in Facebook Groups, Version 2 introduces a full profile-based targeting system, push notifications, and centralized logging — transforming it from a background utility into a purpose-built lead intelligence platform.
Most automation tools stop at monitoring. They don’t scale. They don’t adapt. For freelancers or small agencies juggling multiple services, offers, or regions, a single stream of unfiltered data becomes noise. There’s no structure — and worse, no system for catching high-value opportunities as they happen.
GigHunter V2 introduces the concept of profiles — up to six independent search profiles that allow users to target entirely different client types, niches, or roles simultaneously. Each profile includes unique keyword triggers and group lists, keeping lead discovery clean, separated, and context-aware.
When a match is found, the system:
Sends a real-time push notification to your phone via Pushover
Includes a direct link to the post and a summary of metadata
Automatically logs the lead to a local CSV for record-keeping and follow-up
And it all runs behind the scenes — undetectable by Facebook, frictionless to deploy, and built to adapt to shifting strategies.
GigHunter V2 is more than automation — it’s a tactical layer for client acquisition. Whether you’re targeting music gigs, video projects, design leads, or brand consulting roles, GigHunter lets you split-test strategies, monitor niche opportunities, and stay ahead of the curve without drowning in notifications or fluff. It’s outbound prospecting reimagined — and it’s just getting started.
Contact Us
Let’s Build What’s Next
Real Tools.
No Noise.
Whether you’re looking to integrate an existing tool into your internal workflow, license a solution, or collaborate on something entirely new — we’re open to strategic partnerships that make sense.
Every project in this suite was built to solve a real problem — fast, clean, and without the guesswork. If you see a fit or want to explore something custom, reach out. We don’t do bloated SaaS. We build tools that work.
Got a challenge worth solving?
We’re all ears.
Whether it’s licensing, integration, or something custom — we’re listening.
- 644a rue Sauvé Est, Montreal QC
- [email protected]