Net17 Solutions | AI Web & Mobile Apps
We design and build production-ready web and mobile products where intelligent automation is part of the core architecture—not bolted on later. From customer platforms to internal tools, every layer is built for speed, clarity, and long-term growth.
4.8★
Client rating
4 wks
Typical MVP sprint
24/7
Post-launch support options
Production-ready
Smart architecture from day one
AI-native UX
Automation where it matters
Modern customers expect software that responds instantly, learns from context, and removes friction from everyday tasks. A traditional app stack can deliver features, but it often struggles when workflows grow complex, data volumes increase, or teams need intelligence embedded in the product itself. That is where AI-native web and mobile development changes the equation: your product is designed around automation, personalization, and decision support from the first sprint—not as a phase-two add-on.
At Net17 Solutions, we build web applications with Next.js, React, and Node.js backends, alongside mobile apps using Flutter and native iOS/Android where performance demands it. We integrate large language models, retrieval-augmented generation (RAG), and agentic workflows when they create measurable value: faster support resolution, smarter search, automated document handling, or intelligent onboarding. Every integration is tied to a business outcome, not a demo feature.
Our team works with founders, product leaders, and enterprise stakeholders who need a partner that understands both software craft and AI implementation risk. We run structured discovery, define clear architecture boundaries, and ship in transparent sprints so you always know what is live, what is next, and what metrics we are optimizing for. Whether you are replacing a legacy portal, launching a customer app, or unifying web and mobile experiences under one platform, we deliver systems that scale with your roadmap—not against it.
Product dashboard preview
Replace with your app screenshot or demo video
The challenge
Teams often launch web or mobile apps quickly, then hit walls when traffic grows, integrations multiply, or AI features are requested late in the cycle. Retrofitting intelligence into a brittle codebase costs more than building it correctly upfront. Data silos, inconsistent APIs, and unclear ownership between design and engineering create delays that compound every quarter.
Another common gap is treating AI as a chat widget instead of workflow infrastructure. Support teams still manually triage tickets. Sales still copy data between systems. Operators still export CSVs to answer simple questions. The product works, but the business still carries hidden labor costs that do not show up on a feature checklist—until churn, delays, or competitor pressure force a rebuild.
0%
of product teams rebuild within 18 months due to poor architecture
Capabilities
From UX and engineering to AI integration and cloud deployment, we cover the full delivery path.
We build responsive, SEO-friendly web apps with Next.js and React—optimized for performance, accessibility, and maintainability. Server components, edge caching, and API design are planned early so marketing pages, dashboards, and authenticated experiences share a coherent architecture without duplicate logic.
Flutter and native stacks for iOS and Android let you reach users on every device. We align mobile UX with your web product, share authentication and analytics patterns, and design offline-friendly flows where field teams or consumers need reliability beyond perfect connectivity.
LLM-powered search, assistants, classification, and summarization are implemented with guardrails: prompt versioning, evaluation sets, fallback behavior, and human-in-the-loop review where accuracy matters. We document limitations clearly so stakeholders trust what the system can and cannot do.
Your app connects to CRMs, payment gateways, ERPs, and internal databases through well-defined APIs. We use webhooks, queues, and idempotent jobs where reliability is critical, so third-party outages do not cascade into data loss or duplicate transactions.
Deployments on AWS, Vercel, or hybrid setups include monitoring, staging environments, and CI/CD pipelines. Autoscaling, database indexing, and CDN configuration are part of delivery—not an afterthought—so launch day traffic does not become an emergency.
Post-launch, we help you prioritize roadmap items based on usage data and support patterns. Feature flags, analytics events, and structured feedback loops keep iteration fast without destabilizing production for existing users.
Industries
Multi-tenant dashboards, billing portals, and admin tools with role-based access and embedded AI assistants for onboarding and support.
Product discovery, personalized recommendations, inventory-aware search, and mobile checkout experiences optimized for conversion.
Patient-facing apps and clinician tools with privacy-conscious data handling, appointment flows, and secure document processing.
Replace spreadsheets with unified web and mobile apps for field teams, approvals, and real-time operational visibility.
How we work
We map users, workflows, integrations, and success metrics. Technical constraints and AI opportunities are documented before design commitments.
UX flows, system architecture, and data models are aligned with stakeholders. Prototypes validate critical paths early.
Sprint-based development with demos, code reviews, and automated tests on core flows. AI features ship behind flags when needed.
Production rollout, monitoring, and iteration based on real usage. We refine performance and automation as patterns emerge.
No overengineering. Every layer earns its place in the stack.
Products shipped
Update in config
On-time sprint delivery
Update in config
Average client rating
Engineers on staff
Update in config
Proof
Replace placeholder metrics with your verified project results in config/services.ts.
B2B SaaS | REPLACE
Problem: Legacy web portal slowed onboarding and support teams relied on manual triage.
What we did: We rebuilt the customer portal on Next.js and added an AI assistant trained on product docs.
Result
—
REPLACE: e.g. faster onboarding or support deflection
Consumer mobile | REPLACE
Problem: Separate iOS and Android codebases doubled release effort.
What we did: Unified Flutter app with shared API layer and offline-first catalog browsing.
Result
—
REPLACE: e.g. release cycle or retention metric
Operations | REPLACE
Problem: Field teams used spreadsheets for daily reporting.
What we did: Mobile-first workflow app with real-time sync and admin dashboards.
Result
—
REPLACE: e.g. hours saved per week
Clients
“REPLACE: Add a verified client quote about web/mobile delivery quality and communication.”
“REPLACE: Add a quote about AI features shipping on time and meeting business goals.”
REPLACE metric
Tech stack
Modern, proven tools chosen for maintainability and scale.
FAQ
Timelines depend on scope: a focused MVP with core flows and one AI feature often ships in four to eight weeks. Larger platforms with multiple integrations, roles, and compliance needs typically run twelve to twenty-four weeks in phased releases. We provide a roadmap after discovery with milestone dates, not a single vague estimate.
