Back to home
Case studies

Proof from the field

These are real products we have built and launched: SaaS, AI-heavy platforms, marketplaces, education tools, and more. Much of our work pairs solid engineering with LLMs, automation, and intelligent features. Each story breaks down the problem, our approach, and what went live, in simple language you can skim in a few minutes.

33+ write-upsMulti-vertical

Each preview image matches that project's industry and product type. Full details and tech stack are in the sections beside the image. If a public link exists, you can open the live product.

IndustryMarTech, AI content and SEO automation
AI / SaaS2024

DropPR.ai

We delivered a production-grade MarTech platform for teams that must turn rich media into searchable, publish-ready editorial at volume. The product spans ingestion, async AI pipelines, operator visibility, and growth mechanics so marketing and comms orgs can run campaigns without babysitting infrastructure.

Challenge

The client needed to sustain heavy concurrent transcription and generation without silent failures, while deterring abuse and proving progress to end users. Organic discovery had to stay first-class: metadata, crawlability, and operational SEO could not be bolted on late without rework.

Our approach

We built queue-backed workers, hardened APIs, and structured status surfaces so every job is observable from upload to completion. We layered validation, logging, anti-spam controls, and indexing workflows so the system behaves like an enterprise SaaS surface, not a demo wrapper around a model API.

What we delivered

  • End-to-end pipeline visibility so users and admins always know where content sits in processing, reducing support load and trust gaps.
  • Multi-modal flows spanning audio-to-article, in-browser capture, and AI voiceover so one platform replaces several point tools.
  • In-product messaging, AI-assisted support, and feedback loops that turn production traffic into actionable product intelligence.

Technology stack

AI / LLM orchestrationBackground workers and queuesReal-time job statusAPI hardening and abuse controlsSEO and indexingObservability and logging

Cyverix role

Platform, backend, and product delivery

Visit liveSimilar build
IndustryCommunications, Real-time voice and signaling
Realtime / Comms2024

TalkHub

TalkHub is a communications product that packages WebRTC calling behind enterprise-appropriate authentication and persistence. We treated signaling, presence, and call state as first-class distributed concerns, not a weekend demo, so the experience survives real networks and real user behavior.

Challenge

Browser calling fails when ICE negotiation, NAT traversal, and auth/session drift are handled casually. The client needed predictable call setup, searchable users, online presence, and APIs that resist trivial abuse in a public-facing deployment.

Our approach

We combined Next.js 15 with a custom Node server, Socket.io signaling, STUN/TURN configuration, and MongoDB-backed profiles. Joi validation, bcrypt-backed credentials, JWT-protected routes, and security headers round out a stack that reads like a serious comms MVP ready for hardening and scale-out.

What we delivered

  • User discovery and presence modeling so calls start from real directory state rather than opaque peer IDs.
  • Offer/answer/ICE exchange orchestration with hooks abstracted into maintainable client modules for future mobile clients.
  • Custom React hooks encapsulating WebRTC lifecycle noise so product teams can iterate UI without breaking media logic.

Technology stack

Next.js 15Socket.ioWebRTC / STUN / TURNMongoDBJoi validationJWT and security headers

Cyverix role

Realtime engineering, signaling architecture, and secure APIs

Similar build
IndustryHR Tech, Talent acquisition and CV intelligence
Web / HR Tech2024

GenX Career

GenX Career targets the HR technology vertical with an aggregated discovery experience and AI-assisted application quality. Job seekers operate from one surface while the system reasons about fit, wording, and structure against real postings, reducing spray-and-pray applications.

Challenge

Candidates were bouncing between job boards with inconsistent CV quality and no feedback loop. The product needed credible integrations, fast search, and document generation that feels professional, not gimmicky, because hiring managers judge polish instantly.

Our approach

We connected listings from major sources with one-click apply handoffs where appropriate, built CV analysis flows against posting text, and shipped a template-driven CV builder with export paths. The architecture keeps AI suggestions explainable enough for users to trust edits before submission.

What we delivered

  • Single-pane discovery reducing context switching across external boards while preserving deep links and attribution.
  • Fit-oriented AI commentary tied to specific roles rather than generic “improve your resume” tips.
  • Multiple high-quality document templates with consistent typography and parse-friendly structure for ATS systems.

Technology stack

Next.jsJob feed aggregationLLM CV analysisPDF / DOC generationTemplate engineAnalytics on funnel events

Cyverix role

Product engineering, AI integration, and document workflows

Visit liveSimilar build
IndustryPropTech, Home operations and maintenance
Web / Home2024

HouseHub365

HouseHub365 is a homeowner operations platform in the PropTech space: appliances, warranties, maintenance schedules, and trusted service providers in one system. We treated the home as a portfolio of assets with timelines, not a single static dashboard, so families stop losing manuals and missing service windows.

Challenge

Home data is fragmented across rooms, vendors, paper manuals, and ad hoc reminders. Without structure, even simple maintenance becomes reactive and expensive.

Our approach

We built Next.js with Node and MongoDB, modeling room-wise appliances, smart and manual reminders, verified contractor discovery, and durable service logs. Storage and notification patterns are designed so the product can grow into insurer or property-manager partnerships later.

What we delivered

  • Portfolio-style dashboards that mirror how owners think: by space, asset class, and upcoming maintenance risk.
  • Scheduling intelligence combining manual plans and automated nudges so seasonal and manufacturer intervals are not missed.
  • Verified contractor flows with booking hooks that reduce “random phone number from Facebook” risk for homeowners.

Technology stack

Next.jsNode.jsMongoDBNotification jobsCloud file storageVerification workflows

Cyverix role

Full-stack product engineering for consumer PropTech

Visit liveSimilar build
IndustrySaaS, AI writing and editorial tooling
AI / Content2024

Rewordify AI

Rewordify AI is a SaaS workspace for teams and creators who need controlled rewriting, generation, and file-based editorial workflows. We shipped flows that respect tone, length, and format constraints while keeping exports compatible with downstream legal and marketing review.

Challenge

Generic chat UIs frustrate professional writers: parameters drift, files leak context, and outputs are hard to version. The client needed deterministic-enough controls, ingest for office formats, and admin communication channels for policy updates.

Our approach

We engineered paragraph and document pipelines with explicit parameter panels, PDF/Word/text ingest, exports to .txt and .doc, and guided onboarding content. Admin messaging surfaces let operators broadcast changes to acceptable use or model behavior without redeploying static copy only.

What we delivered

  • Tunable tone and length targets so teams can enforce brand voice instead of post-hoc editing everything.
  • Sample-driven onboarding and one-click copy flows that reduce time-to-first-success for non-technical users.
  • File ingest with sensible guardrails so large documents do not destabilize client memory or server timeouts.

Technology stack

LLM content APIsPDF / DOC parsingNext.js or SPA clientJob chunking for long docsExport pipelinesAdmin messaging

Cyverix role

Product engineering for AI-assisted content SaaS

Similar build
IndustrySaaS, Multimodal generative AI suite
AI / Creative suite2024

Smart Transform AI

Smart Transform AI is a unified creative suite spanning text-to-video, text-to-image, text-to-voice, voice-to-text, and image-to-text with admin analytics. We packaged multiple modality endpoints behind one product identity so teams stop juggling five single-purpose tabs.

Challenge

Multimodal UIs become confusing fast: users lose track of which model ran, which credits burned, and where outputs live. Operators need aggregate visibility to tune pricing and capacity.

Our approach

We implemented a Next.js and Tailwind client with a centralized admin dashboard for activity logs, statistics, and behavioral insights. Tool routes share consistent progress, error, and history patterns so the suite feels intentional, not a bundle of iframes.

What we delivered

  • Five conversion tools with shared session, billing, and history semantics for lower support overhead.
  • Admin analytics on usage spikes that inform which modalities need rate limits or model upgrades.
  • Workflow defaults that guide non-technical creators through safe prompts and file prep steps.

Technology stack

Next.jsTailwind CSSMultimodal AI APIsAdmin analytics DBJob trackingAuth and quotas

Cyverix role

Full-stack AI suite engineering and instrumentation

Similar build
IndustryTravel and hospitality, Flexible rentals and splits
Marketplace2024

PaceDream

PaceDream addresses a complex slice of the travel and short-term rental industry: hourly inventory, roommate economics, and distressed inventory for last-minute trips. We engineered unified booking and payment semantics so radically different inventory types do not fork into unmaintainable code paths.

Challenge

The business combined rooms, restrooms, parking, roommate splits, and flash deals, each with different risk profiles. Users still expect Airbnb-grade trust cues, fair refunds, and security around payments.

Our approach

We implemented cohesive booking flows with optional authentication where it improves conversion, explicit credit/refund rules, and payment security messaging. The architecture isolates pricing and inventory rules per vertical while sharing a single cart and ledger conceptual model.

What we delivered

  • Hourly rental support across unconventional inventory categories without compromising checkout clarity.
  • Roommate split-payment flows that reduce awkward peer-to-peer money chasing outside the platform.
  • Last-minute travel merchandising hooks for flights and lodging with operational safeguards on inventory freshness.

Technology stack

Marketplace corePayments and ledger rulesInventory modelingFraud-conscious checkoutNotification systemAdmin pricing tools

Cyverix role

Platform engineering, payments logic, and marketplace UX

Visit liveSimilar build

Planning something comparable?

Share your limits and timeline. We will reply with a straight answer on fit, tech, and how we would deliver.

View all servicesStart a project