Agents with workflow boundaries
Support, operations, booking, and internal-tool agents need retrieval, tool permissions, approval gates, traces, and evaluation rather than open-ended chat.
AI product engineering studio
AI products, agents, and SaaS platforms built as production systems.
Svorus designs and engineers AI-powered applications, LLM workflows, mobile products, backend platforms, and cloud-native systems for teams that need serious software to ship.
AI StrategyAgentic AIProductCloud and DevOpsDataInteractive
AIagents, LLM workflows, vision, and automation
Full-stackmobile, web, backend, data, and cloud delivery
Productsin-house builds and case studies used as proof
AI capabilities
Start with the AI work users will actually touch, then prove it in product context.
The homepage should move from positioning into concrete AI capability areas before showing Svorus-owned products and selected portfolio work.
LLM and RAG systems with source discipline
Document intelligence, copilots, and knowledge workflows are strongest when answers stay tied to indexed sources, metadata, permissions, and freshness.
AI product surfaces, not isolated demos
Nutrition, wellness, coaching, vision, and automation features need mobile and web UX, backend state, cloud operations, monitoring, and privacy controls.
Svorus products
In-house products make the engineering claims inspectable.
Eleviy and Loveton show how Svorus approaches mobile UX, backend architecture, AI workflows, subscriptions, cloud integrations, and product operations in owned systems.
Svorus productIn-house product
Svorus-owned productEleviy: AI fitness and nutrition product
Eleviy is a Svorus-owned AI fitness and nutrition product with a Flutter mobile app, FastAPI backend, multimodal meal analysis, personalized coaching, and workout generation.
FlutterRiverpodGoRouterDrift
Svorus-ownedin-house AI fitness and nutrition product
Multimodal AImeal photo analysis, coaching, and workout generation
Svorus productIn-house product
Svorus-owned productLoveton: mobile-first relationship app for couples
Loveton is a Svorus-owned couples app with a Flutter mobile experience, FastAPI backend, real-time partner interactions, shared rituals, mini-games, subscriptions, notifications, and media workflows.
FlutterRiverpodGoRouterDrift
Svorus-ownedin-house consumer relationship product
Real-timecouple events, presence, canvas, messages, questions, photos, countdowns, and kisses
Selected work
Case-study and lab entries connect AI claims to specific systems.
Glowskin is presented as a portfolio case study, while lab and prototype entries are labeled as internal R&D directions so visitors can separate shipped work from research concepts.
Case studyPortfolio case study
GlowskinGlowskin: AI skin and hair coaching platform
Glowskin is an AI skin and hair coaching case study with a Flutter mobile app, FastAPI backend, Gemini image analysis, routine generation, ingredient scanning, subscriptions, tracking, and compliance pages.
FlutterRiverpodGoRouterDio
AI visionskin, hair, and cosmetic label analysis with Gemini and MediaPipe-assisted concern zones
Full-stackFlutter app, FastAPI backend, PostgreSQL data model, S3-compatible media, Firebase, Razorpay, and compliance website
Svorus LabInternal R&D concept
Svorus LabSupportOps Agent: AI support workflow lab
SupportOps Agent is a Svorus Lab concept for AI-assisted support operations with ticket triage, retrieval, tool calls, human approval gates, and agent observability.
OpenAI Agents SDKNext.jsFastAPIPostgreSQL
Lab conceptnot represented as shipped client work
AgentOpstraces, approvals, evaluation, cost, latency, and tool-failure monitoring
PrototypeInternal prototype concept
Svorus LabVoice Booking Agent: realtime AI calling prototype
Voice Booking Agent is a Svorus prototype concept for realtime AI calling with slot extraction, calendar and CRM tools, transcript review, and human handoff controls.
LiveKit AgentsOpenAI Realtime APITwilioFastAPI
Prototypelab-ready concept for voice AI validation
Realtimevoice loop, slot extraction, tool calls, calendar state, and human handoff
Services
AI engineering, product engineering, and cloud architecture in one loop.
The service model is organized around what sophisticated products actually need: intelligence, interfaces, APIs, data, deployment, and operations moving together.
AI Strategy and AdvisoryBoard-ready AI roadmaps, operating models, and ROI filters before teams spend on pilots.View serviceAgentic AI and Applied AI EngineeringProduction AI agents that plan, use tools, and act with evaluation, logging, and human oversight.View serviceProduct Engineering and Custom SoftwareWeb, mobile, and platform engineering from discovery through production with one accountable team.View serviceCloud, DevOps and Platform EngineeringCloud migration, CI/CD, observability, reliability, and platform foundations built for on-call reality.View serviceData Engineering and AnalyticsTrusted pipelines, data platforms, BI, and MLOps foundations for products, dashboards, and AI agents.View serviceInteractive and Game Development2D, 3D, HTML5, AR, VR, multiplayer, and live-ops engineering for real-time experiences.View serviceDedicated Teams and Staff AugmentationNamed engineers embedded in your rituals, repos, and delivery process instead of an anonymous ticket queue.View serviceManaged Services and SupportApplication, cloud, and AgentOps support from the team that understands what was built and why.View service
One partner, not five vendors
AI features fail when they are treated as isolated demos.
Svorus connects model behavior, product UX, backend contracts, data quality, cloud operations, and release ownership from the start.
AI strategy stays tied to working software
Agent, RAG, automation, and vision ideas are shaped around the APIs, data, permissions, latency, cost, and safety controls needed for production.
Product engineering carries the operating context
Mobile, web, backend, cloud, and observability decisions are made together so features can be shipped, debugged, improved, and owned.
Portfolio proof comes from real systems
Eleviy, Loveton, and Glowskin should show architecture, workflows, AI pipelines, integrations, and product surfaces rather than generic agency claims.
The Svorus Method
A delivery rhythm that starts before code and continues after launch.
- 01
Diagnose
Map the technical, business, data, and operating reality before the first sprint is committed.
- 02
Design
Define architecture, prototypes, success metrics, and release slices before production work begins.
- 03
Ship
Build inside your repos and cloud accounts with weekly demos, scoped sprints, and visible tradeoffs.
- 04
Operate
Run the system as a managed service or hand it over with knowledge transferred sprint by sprint.
Industries
Focused patterns for markets where software has to hold up.
The industry pages connect real workflow pressures to the Svorus services most likely to matter.
Fintech and Financial ServicesAI, data, product, and cloud systems for regulated financial workflows.Healthcare and Life SciencesWorkflow, data, and AI engineering for privacy-aware healthcare systems.Logistics and Supply ChainOperational software, data, and AI for visibility, routing, and exception handling.Media, Entertainment and GamingReal-time product, live-ops, data, and interactive engineering for audience businesses.Retail and EcommerceCommerce engineering for conversion, inventory, personalization, and operations.SaaS and Digital-Native StartupsProduct, platform, AI, and data engineering for teams that need velocity with discipline.
Testimonials
No invented quotes.
Testimonials will stay empty until real clients can speak.
Svorus will not publish fabricated endorsements or placeholder names that look real.
Insights
Early notes from the Svorus build floor.
Short, practical writing on AI agents, delivery, cloud, data, and product engineering.
DeliveryProduct Engineering
One partner instead of five vendors
The real cost of fragmented delivery is not only markup. It is the lost context between strategy, software, cloud, data, and operations.
AIAgentic AI
Shipping AI agents with boundaries
Production AI agents need clear jobs, scoped tools, evaluation, and human control before they are allowed to act.
Bring us the AI product or platform problem.
We will help frame the workflow, architecture, model behavior, integration path, and first responsible release slice.