Vynnter is a software engineering company building native mobile apps, scalable backends, and production AI automation for startups, small and medium businesses, and enterprises.
Native mobile apps, the backends behind them, and AI that removes busywork — from first build through launch and long-term support, with a clean handover whenever you want it.
Native Swift and Kotlin apps engineered for each platform — not ports. Shared KMP or Flutter codebases where they're the better trade-off.
Secure, cloud-native backends built to stay reliable as traffic, data, and integrations grow.
Production AI, not demos: agents, copilots, and automation shipped with evaluation suites — reliability measured before launch, not assumed.
Software is a living system, and we stay engaged after launch. Long-term partnership is the default engagement model, not an upsell.
Not sure which of these your project needs? Describe the problem and we'll explain how we'd approach it.
Discuss your projectRun by the engineers who write the code, Vynnter works as an extension of your team — not a project shop that disappears after handoff.
Swift on iOS, Kotlin on Android — cross-platform only when it's genuinely the right trade-off.
Built for your next stage of growth and shipped with monitoring, rollback paths, and load headroom — on boring, proven foundations until scale demands otherwise.
Threat modeling, dependency audits, and least-privilege infrastructure are part of the definition of done — never bolted on before launch.
Every LLM feature ships with evaluations, guardrails, and fallbacks — systems your operations can depend on, not prototypes that stall.
Full IP transfer, repositories you control from day one, and codebases any competent team can maintain. No lock-in, by design.
Clear timelines, honest estimates, a weekly update with a test build you can actually use, and trade-offs explained in plain language. No surprises on the invoice.
Vishvanath Eshwer
Founder & Engineer
Over ten years building native and cross-platform apps, the backends behind them, real-time systems, and the admin and monitoring tooling teams run on. The engineer you talk to during scoping architects the system and reviews every line that ships.
Chosen for reliability and longevity, not novelty. These are our defaults — we also work in the stack you already run.
We design AI systems that plug into how your team already operates, and hand control back to humans exactly where it matters.
AI agents that resolve routine tickets, draft responses from your knowledge base, and escalate edge cases to a human queue with full context attached.
Order processing, scheduling, and back-office workflows that run themselves, with human approval gates exactly where your process needs them.
Extract, classify, and act on invoices, contracts, and forms, turning document backlogs into structured data your systems can use.
Assistants grounded in your company's data that answer policy questions, draft documents, and retrieve answers your team currently hunts for manually.
Multi-step agentic pipelines built on LangGraph that coordinate tools, APIs, and approvals: observable, auditable, and recoverable at every step.
Ask questions of your own data in plain language. These assistants query your warehouse and return answers with the numbers to back them.
From first conversation to production and beyond: the same disciplined path on every engagement.
We understand the problem, constraints, and success criteria before writing a line of code, then scope the work into a fixed estimate that says what to build now and what to defer.
We design a system that scales with your business, not against it: data models, service boundaries, security posture, and infrastructure planned up front.
We build in focused, reviewable increments: a written update every week, and a test build to try whenever there is something worth trying. You judge progress by using the product, not by reading about it.
We ship to production with monitoring, rollback paths, load testing, and a security review baked in. Launch day is uneventful by design.
We stay engaged post-launch: performance tuning, security patching, infrastructure scaling, and a roadmap of new capabilities as your product grows.
Different domains, same discipline: secure data, reliable integrations, and systems that hold up under real operations.
Payment platforms, ledger systems, and compliance-aware backends.
Multi-tenant platforms, subscription billing, and usage analytics.
Patient-facing apps and privacy-conscious clinical data pipelines.
Fleet tracking, route optimization, and real-time operations dashboards.
E-commerce backends, inventory systems, and point-of-sale integrations.
Internal platforms, workflow automation, and legacy system modernization.
Client portals, scheduling systems, and document automation.
Portfolio and personal sites for public figures, founders, and creators — with booking, media, and audience data handled properly.
Straight answers on cost, timelines, LLM integration, and who owns the code.
A single-platform app with a simple backend, covering development through deployment, starts at ₹1 lakh — scoped to an agreed screen count and standard integrations. A production app with its own backend, authentication, and an admin panel typically runs ₹4 lakh to ₹10 lakh; full platforms range from ₹10 lakh to ₹25 lakh and above depending on scope, integrations, and compliance. Every tier ships a working system in production, not a prototype you finish yourself, and the code is yours from day one. Ongoing support is quoted separately from the build, typically 15–25% of build cost per year. Figures exclude GST. After a discovery call we send a fixed-scope estimate: what to build now, what to defer, and where cross-platform or off-the-shelf components cut cost without hurting the architecture.
A focused single-platform build ships in 3 to 5 weeks, and a production app with its own backend, authentication, and an admin panel in 6 to 10 weeks. Discovery and architecture take the first week; after that you get a written update every week and a test build — on your own device, or a staging link for backend work — whenever there is something worth trying, so you are using the product as it is built rather than reading about it. Code generation is genuinely fast now, and we build with the same AI tooling we ship for clients, but what sets a timeline is integration work, your review cycles, security hardening, and store approval, none of which compress. Larger platforms and anything touching regulated data run longer, and we say so in the estimate rather than mid-project.
Yes. Integrating models from Anthropic and OpenAI into existing products is one of our core services. We build LLM features on LangGraph and the Model Context Protocol (MCP), add retrieval-augmented generation (RAG) over your data, and ship every AI feature with an evaluation suite so accuracy is measured, not assumed. Your existing backend and data stay where they are; we integrate around them.
Both. We work with startup founders, small and medium businesses, and enterprise teams. Startups get senior engineers who design an architecture that survives growth instead of demanding a rewrite at scale. Enterprises get a partner comfortable with security review, compliance constraints, and integrating with existing systems and legacy platforms.
You do. Every engagement transfers full ownership of the source code, infrastructure configuration, and documentation to you, held in repositories you control from day one. There is no lock-in: the codebases we deliver are written to be maintained by any competent engineering team, not just by us.
Yes. Long-term support is our default engagement model, not an add-on. After launch we provide monitoring and observability, performance optimization, security patching, infrastructure management, and continuous feature development under a monthly partnership arrangement, typically 15–25% of the original build cost per year. You can also hand the system to an in-house team at any time; we document for that from the start.
Tell us what you're building. Vynnter's engineering team reads every enquiry and responds within one business day.
We come back with questions and a proposed time for a 30-minute call. No sales deck.
We map requirements, constraints, and architecture options with your team.
A written plan covering timeline, cost, and what we'd defer, yours to keep either way.
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