Every question founders ask before working with us

Nexios Technologies LLP is headquartered in Surat, Gujarat, India. We work with clients across the US, UK, Europe, and the Middle East, with a 4–5 hour overlap with US East Coast time for standups, sprint reviews, and urgent communication. All project communication is in English.

Nexios specializes in three industries: healthcare and telehealth (HIPAA-compliant platforms, EHR integrations, care coordination), e-commerce and D2C (custom marketplaces, Shopify Plus, subscription platforms), and concierge and luxury (bespoke CRM platforms for luxury watch and jewellery retail). We also build AI-powered products across all three verticals.

Nexios Technologies LLP was founded in 2017. We have 8+ years of experience in product engineering, a team of 40 engineers, and have shipped 100+ products for founders and companies across 12+ countries.

Yes, the majority of our clients are US-based founders and startups. We maintain a 4–5 hour overlap with US East Coast time for standups, sprint reviews, and urgent communication. All project communication is in English.

Domain knowledge. We understand what an ADT event is, what an IDG meeting involves, what a healthcare staffing agency's credentialing burden looks like, and why a generic AI chatbot in a clinical setting is dangerous. We have shipped real software — in healthcare, e-commerce, and luxury retail — that runs in production for actual users. We do not relearn your industry on your project budget.

Yes. HIPAA compliance is built into the architecture from day one — not added as a checklist at the end of the project. This means encryption in transit and at rest, role-based access control, audit logging on all PHI access, and BAA-ready infrastructure. We have shipped a HIPAA-compliant production platform (CareCoordinations) for a US home health client with real patients and clinicians using it daily.

Yes. We have built bidirectional HCHB integration in production, including ADT event feeds (admit, transfer, discharge), MDM attachment synchronization, and real-time two-way data sync. The same integration patterns generalize to HL7- and FHIR-based data exchange with other EMR and EHR systems. If your EMR has an API or supports standard healthcare data formats, we can build to it.

Yes. Our most significant healthcare engagement was for a US-based home health startup. We built their care coordination platform from the ground up — full HCHB integration, native iOS and Android apps for field clinicians, IDG meeting support, and an AI-powered knowledge assistant. We understand the clinical workflows, compliance requirements, and operational realities of home health because we have lived them on a real project.

It depends on the scope. A fixed-scope MVP with defined requirements typically takes 8 to 16 weeks. A more complex platform with EMR integration, mobile apps, and AI features takes 4 to 6 months. For ongoing product development, a dedicated team engagement is more appropriate than a fixed-price contract. We give accurate timelines after a proper scoping conversation, not before.

Yes. We have shipped HIPAA-compliant iOS and Android apps for US home health clinicians. This means encrypted local storage, secure authentication with biometric support, audit logging on PHI access, and BAA-ready backend infrastructure. We understand what HIPAA requires at the mobile layer — not just the server layer — because we have built and shipped it in production.

Yes. We build production AI products including RAG pipelines, AI agents using LangChain and CrewAI, LLM integrations with OpenAI, Claude, and Gemini, AI workflow automation for document processing and data extraction, and computer vision for image pipelines. We have shipped multiple AI products in healthcare and e-commerce that handle real production load daily.

RAG stands for Retrieval-Augmented Generation. It is the architecture that makes AI answer from your actual content instead of guessing. Without RAG, an LLM will hallucinate product names, prices, and facts that do not exist. With RAG, the system retrieves your real content first, then generates an answer grounded in it — every response is traceable to a source document. For any customer-facing or business-critical AI, RAG is not optional.

We use several techniques in combination. RAG architecture grounds responses in source documents so the model cannot invent facts. Confidence thresholds return "I don't know" rather than a confident wrong answer. Source attribution shows users exactly where each answer came from. For healthcare specifically, we add guardrails: responses that touch clinical decisions are flagged for human review. Hallucination prevention is an architectural concern, not a prompt-engineering trick.

Yes. We integrate AI into existing systems — this is most of what we do. We have added RAG-powered knowledge assistants to existing Laravel and PHP platforms, integrated OpenAI APIs into live products, and built AI pipelines on top of existing databases. If you have an existing system, we can extend it with AI without a full rebuild. The typical engagement starts with a scoping session to identify where AI creates real value versus where it adds complexity without benefit.

We use the right model for the task. GPT-4o for complex reasoning and function calling, Claude for long-context document analysis, OpenAI embeddings (text-embedding-3-large) for semantic search, and open-source models where on-premise or cost constraints require it. We are model-agnostic and recommend based on accuracy, latency, and cost requirements — not vendor preference.

It depends on the use case. AI delivers strong ROI on tasks with high volume, variable inputs, and clear success criteria — document processing, knowledge Q&A, content classification, and product recommendations. It is the wrong fit for tasks requiring nuanced judgment calls, legal liability, or real-time physical operations. Book a discovery call and we will give you an honest assessment of where AI would actually help versus where it would add complexity without value.

Both, and we recommend based on your scale and requirements. Shopify is right when its capabilities match your needs and speed to market matters. Custom development is right when your workflows, pricing logic, or customer experience have outgrown what Shopify plugins can do — or when you need marketplace logic, multi-vendor functionality, or deep integrations that Shopify cannot support. We help you make that call honestly.

Yes. We have production experience with the eBay Developers SDK, including seller APIs, listing management, and order ingestion. We have also worked with the Amazon SP-API for marketplace operations. These are bidirectional integrations — not read-only data pulls — syncing inventory, pricing, and order status in real time.

Yes. We built an automated pipeline for a US-based watch retailer that processes 1,500+ product images per week: background removal via ML model, image optimization, and direct upload to AWS S3. It reduced a 3-day manual backlog to under 5 minutes per batch, at 80% lower cost per image than manual processing. If you have a repetitive image or media workflow, we can likely automate most of it.

Yes. We built a bespoke CRM and back-office platform for a UK-based luxury watch and jewellery retailer, covering new and pre-owned inventory, repair workflows from intake to collection, staff attribution, client profiles, and auction sourcing. The client saw 30% year-on-year revenue growth in the year after launch. We understand luxury retail specifics — serial tracking, provenance, condition grading — not just generic CRM concepts.

A Shopify agency works within the platform. We build what the platform cannot do: custom multi-vendor marketplaces, post-sale customer data platforms, automated image processing pipelines, and AI tools grounded in your product catalogue. When your business logic has outgrown what any off-the-shelf tool can handle, that is when you hire us.

For most backend-heavy web apps and SaaS products, we reach for Laravel (PHP) or Node.js. For frontend-heavy products and marketing sites with server rendering, Next.js with React. For mobile, React Native for most cross-platform projects, native Swift or Kotlin when performance or OS integration demands it. We recommend a stack based on your existing codebase, your team's long-term maintenance reality, and the actual requirements — not what is currently trending.

It depends on your budget, timeline, and requirements. Native (Swift and Kotlin) gives you the best performance and deepest OS integration but requires maintaining two separate codebases. React Native and Flutter share most of the code and cut build time by 30–50%, with a small performance trade-off. For most products, cross-platform is the right call. We will give you an honest recommendation after understanding your specific situation.

Yes. We have rescued several projects with poor architecture, no tests, and no documentation. We audit the codebase first, give you an honest assessment of what is salvageable and what is not, and propose a remediation plan with clear priorities. We will tell you if a rewrite makes more economic sense than a rescue.

Yes. We have built multi-tenant platforms with per-tenant data isolation, subdomain routing, role-based access control, subscription billing via Stripe, usage metering, and white-label capabilities. Multi-tenant architecture is a meaningful part of what we do, and we understand the data isolation trade-offs, the operational complexity, and the performance implications.

Yes. We handle the full submission process: provisioning profiles, signing certificates, App Store Connect setup, Google Play Console configuration, store listing assets, and review guidance. We have been through the review process many times and know what Apple and Google reviewers flag. First-submission approval is the goal, not the exception.

Nexios offers three engagement models. Fixed-scope projects start at $8,000, suitable for MVPs and well-defined builds where scope is clear upfront. Dedicated teams are $2,500 per developer per month, best for evolving products, long-running engagements (3+ months), and teams that want a consistent squad. Staff augmentation is $20 per hour with a minimum of 80 hours per month, to fill specific skill gaps in an existing team. All prices are in USD.

We document scope clearly before we start. Scope changes are acknowledged, costed, and either accepted or deferred — they do not silently expand the project and then blow up the timeline at delivery. For open-ended products where requirements evolve, a dedicated team engagement is more honest than a fixed-price contract. We are direct about this in the scoping conversation.

Book a free discovery call. No sales pitch — we ask about your product, your timeline, your existing stack, and your constraints. After the call, we send a proposal within 48 hours covering scope, timeline, team composition, and cost. If it fits, we kick off with a discovery sprint to nail down the technical architecture and detailed requirements before any production code is written.

Yes. We sign mutual NDAs before any detailed technical discussion. We also sign BAAs for healthcare projects, as required by HIPAA for business associates. These are standard for us and we turn them around quickly — typically within 24 hours of receiving the document.