Novaryn

Pricing

Start with the audit. It pays for itself or it saves you a quarter.

Every rupee of the audit is credited against the build that follows, so the worst outcome is a costed report telling you not to bother — which is worth more than the fee.

  • AI Audit

    Find out what can actually be automated

    ₹25,000

    Starting at ₹25,000 · credited in full against any build that follows

    Businesses that know they have too much manual work but cannot yet say which part is worth fixing first.

    • Structured process discovery across every department
    • AI Automation Score with the workings shown
    • Ranked opportunities with hours saved and annual cost
    • ROI, difficulty and implementation estimate per opportunity
    • A written AI Opportunity Report you own
    • A ninety-minute walkthrough with the engineer who wrote it

    Typically 1–2 weeks

    Start the audit

  • AI QuickStart

    Most chosen

    One process, in production, in a month

    ₹75,000

    Starting at ₹75,000 · fixed scope, fixed price

    Businesses with one obviously expensive process, who want proof before committing to a programme.

    • Everything in the AI Audit
    • One AI employee, built and deployed to production
    • Up to three system integrations
    • Knowledge base built from your own documents
    • Human approval policy configured to your risk appetite
    • Execution logs, cost tracking and alerting
    • Thirty days of support after go-live

    Typically 3–5 weeks

    Talk about AI QuickStart

  • AI Transformation

    A department, rebuilt around AI systems

    ₹2,50,000

    Starting at ₹2,50,000 · scoped from the audit

    Businesses ready to automate a whole function — support, finance or the top of the funnel — rather than a single task.

    • Everything in AI QuickStart
    • Multiple AI employees working together
    • Workflow automation across departments
    • Unlimited integrations, including custom APIs and MCP servers
    • Evaluation datasets and staging-to-production promotion
    • Role-based access, audit logging and data retention policy
    • Team training and runbooks
    • Ninety days of support after go-live

    Typically 8–14 weeks

    Talk about AI Transformation

  • Managed AI Operations

    We run what we built

    Custom

    Custom monthly — priced on agents in production and execution volume

    Businesses running AI in production who would rather not hire a team to keep it running.

    • 24/7 monitoring of every agent and workflow
    • Incident response against an agreed SLA
    • Prompt, model and routing optimisation
    • Cost optimisation with a monthly savings report
    • Continuous workflow improvement
    • Quarterly business review against measured ROI
    • A named engineer who knows your estate

    Typically Ongoing

    Talk about Managed AI Operations

Questions

The things people actually ask

Every answer below is the same text the on-site assistant works from, so the two cannot disagree. Press ⌘K if your question is not here.

What does Novaryn actually do?

Novaryn is an AI engineering company. It designs, builds and operates the AI agents and workflows that run repetitive work inside a business — connected to the systems that business already uses. The engagement starts with an AI audit: a structured assessment of how the business actually runs, which produces an AI Automation Score and a ranked, costed list of automation opportunities. Customers can stop there and keep the report, or move on to a build, and eventually to managed operations where Novaryn runs the systems it built. It is not a chatbot vendor. The distinction that matters is reach: agents hold scoped, audited credentials to systems of record, so the work finishes where the work lives rather than as text somebody pastes somewhere. Novaryn also builds and runs 2 products of its own — TechHub.cafe and CardCopilotAI — which is the evidence for the claim rather than the business model. It is owned by Abdul Qadir Khan and can be reached at aqadirkhan93@gmail.com.More on what novaryn is

How is the automation score calculated?

The AI Opportunity Scanner is a free, self-serve assessment at /scanner. Five questions about how a business runs — industry, headcount, systems, volumes and which processes are manual — produce an AI Automation Score out of 100, a ranked list of automation opportunities, and a phased roadmap. The score is a weighted composite: opportunity density (45%), systems readiness (30%), process clarity (15%) and automation headroom (10%). Each term is shown with its weight in the result. No language model is involved in the scoring. The engine is pure arithmetic over a library of costed processes, so the same answers always produce the same figures and every number can be traced back to an input. A model asked to estimate savings produces a confident number that cannot be reproduced or audited. Every report ends with an explicit list of what was assumed, including that default staff costs were used unless the customer supplied their own, and which processes were inferred rather than named. Automation potential is capped below 100% for every process — something always needs a person. Nothing is stored unless the visitor asks for the report to be sent. The scoring runs in the browser.More on the ai opportunity scanner

What can actually be automated?

Novaryn works from a library of 12 business processes, each with a measured manual effort, an automation potential, a build difficulty and an implementation estimate: Lead qualification (88% automatable, 3 weeks); Customer support (72% automatable, 5 weeks); Email processing (76% automatable, 2 weeks); Reporting (94% automatable, 3 weeks); Invoice processing (86% automatable, 4 weeks); Document processing (83% automatable, 5 weeks); Manual data entry (81% automatable, 3 weeks); CRM updates (85% automatable, 2 weeks); Repetitive approvals (68% automatable, 4 weeks); Internal knowledge discovery (74% automatable, 3 weeks); Data reconciliation (89% automatable, 4 weeks); Meeting follow-ups (79% automatable, 2 weeks). These are the same records the scanner scores against, the same ones that become line items in a proposal, and the same ones assigned to an AI employee at build time. Nothing is re-entered between the audit and the deployment.More on what novaryn automates

What stops an agent doing something it shouldn't?

Every production workflow supports human approval, and risk is a property of the action rather than of the model's confidence — a model that is certain it should issue a refund is exactly the case the gate exists for. Actions are classified low, medium or high. Low risk executes automatically; medium asks for approval; high requires it. An action is high risk if it is irreversible, exceeds a rupee ceiling the customer sets, affects more than fifty records at once, or calls a tool on the always-gated list — payments, deletions, credential writes and anything published externally. Pending approvals appear in an approval inbox showing the proposed action, the agent's reasoning, the input, the risk level and the tool being called. An approver can approve, reject, edit before approving, or let it expire.More on human approval and risk

Which systems can you connect to?

Novaryn ships 18 connectors in production, 6 in beta and 2 planned: Gmail (live), Outlook (live), Slack (live), Microsoft Teams (beta), WhatsApp Business (beta), Salesforce (live), HubSpot (live), Zoho CRM (beta), Google Drive (live), OneDrive (beta), Notion (live), Google Calendar (live), Google Sheets (live), Confluence (planned), GitHub (live), GitLab (planned), Jira (live), Zendesk (live), PostgreSQL (live), MySQL (live), MongoDB (beta), Shopify (beta), REST API (live), MCP servers (live), Inbound webhooks (live), S3-compatible storage (live). Any REST API and any MCP server can also be connected, and custom connectors are part of a build rather than an add-on. Each connection supports OAuth or API-key authentication, connection health checks, scoped permissions and usage logs. Credentials are stored by reference in a secret store, never in a row an application query can reach. The status on each connector is shown honestly on the site. A grid of logos where a third of them do not work survives exactly one sales call.More on integrations

What does it cost?

AI Audit: from ₹25,000 — Find out what can actually be automated, typically 1–2 weeks. AI QuickStart: from ₹75,000 — One process, in production, in a month, typically 3–5 weeks. AI Transformation: from ₹2,50,000 — A department, rebuilt around AI systems, typically 8–14 weeks. Managed AI Operations: custom monthly pricing — We run what we built, typically ongoing. The audit is priced rather than free, and credited in full against whatever is built afterwards. A free audit attracts people who want a document and gives us no reason to spend two days on it; charging for it and crediting it back aligns both sides. Pricing is configurable by Novaryn without a deploy, so the figures shown on the site are the current ones.More on pricing

How is our data kept separate from other customers'?

The platform is multi-tenant from the first migration. Every tenant-owned row carries an organisation id, enforced in application code and again by row-level security in the database — two independent mechanisms, because cross-tenant leakage is the one failure that cannot be apologised for. Access inside an organisation is governed by six roles (owner, admin, manager, developer, operator, viewer) resolved against a single permission matrix rather than scattered checks. No role below admin can read a stored credential, and every significant action is written to an append-only audit log. Data retention is configurable per organisation. Knowledge-base retrieval is permission-aware, so an agent answering for one user cannot surface a document that user could not open themselves.More on how customer data is handled

Which parts are built, and which are only planned?

Being precise about this matters more than sounding impressive. Working today: the design token system and the theme engine, both with test suites, plus this website. The component library is started — a handful of primitives, not a full kit. Specified but not built: the platform kernel (identity, organisations, RBAC, billing, usage metering, audit log) and the AI gateway. Those are written down as architecture, not shipped as code. Next in order of leverage: the command palette as a shared component across every product, data-visualisation primitives, then a unified console where one account reaches all of them.More on what is actually built

What is it all built with?

The Novaryn monorepo is pnpm workspaces plus Turborepo, on Node 22+, TypeScript in strict mode. The website is Next.js 16 with React 19 and Tailwind CSS v4. Tailwind v4 specifically, because it is CSS-variable-native and the theme engine depends on that — `@theme inline` keeps every utility a live reference to a custom property instead of baking in a value. The products themselves are Next.js apps on Postgres, mostly with pgvector, deployed on Vercel and Render. They vary: four are on Tailwind v3 today, which is the main friction in adopting the design system. This assistant runs on Claude Opus 5 via the Anthropic API, grounded on a knowledge base generated from the design system's own source.More on the technology

How do I get in touch?

Novaryn is built by Abdul Qadir Khan. The email address for anything — partnerships, support, press, or a technical question — is aqadirkhan93@gmail.com. Each product also has its own site, listed on the products page, and support for a specific product is best raised there.More on getting in touch

Next

Find out what your business could automate

Start with the audit. You get a costed, ranked opportunity list — and you keep it whether or not you build anything with us.

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