Novaryn

AI automation & intelligent operations

AI systems thatrun your operations.

Novaryn designs, builds and operates the AI agents and workflows that run repetitive work across your business — connected to the systems you already use.

We start by finding what is actually worth automating. You get the number before you get the invoice.

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Four minutes, no call required. You keep the report either way.

How the work actually flows

  1. Business data

    • Email
    • Documents
    • CRM records
    • Tickets
    • Databases

  2. Novaryn AI

    • Retrieval
    • Extraction
    • Reasoning
    • Decision

  3. Agents & workflows

    • AI employees
    • Triggers
    • Tools
    • Human approval

  4. Your systems

    • HubSpot
    • Slack
    • Drive
    • Postgres
    • WhatsApp

  5. Automated operations

    • Monitored
    • Costed
    • Audited
    • Improving
AI employees
6AI employeessales, support, finance, ops, research, reporting
integrations
26integrationsCRM, mail, chat, drives, databases, MCP
of high-risk actions gated
100%of high-risk actions gatedhuman approval, by default
to a costed opportunity list
4 minto a costed opportunity listno call required

Built and operated by Novaryn

Five live AI products. No customer logos — Novaryn is early, and these are its own.

The problem

Your team is doing work a system should be doing

Not the interesting part of anyone's job. The part that happens between the interesting parts — reading, copying, checking, chasing, and typing the same thing into a second system.

  • Lead qualification

    sales

    A rep opens each enquiry, searches the company, guesses at fit, and types a summary into the CRM — or doesn't, which is worse.

    88% automatable · 3 weeks to production

  • Customer support

    support

    An agent reads every ticket to discover that two thirds of them are the same six questions, then writes the same six answers again.

    72% automatable · 5 weeks to production

  • Email processing

    operations

    Someone is the human router for a shared inbox. It is nobody's job title and it is four hours of their week.

    76% automatable · 2 weeks to production

  • Reporting

    operations

    Exports into a spreadsheet, a pivot table, a paragraph of commentary, and an email. Every week, by a person who is good at something else.

    94% automatable · 3 weeks to production

  • Invoice processing

    finance

    A finance assistant opens a PDF, types eleven fields into the accounting system, and checks a total against an email.

    86% automatable · 4 weeks to production

  • Document processing

    operations

    Reading a document to copy eight fields out of it, then reading it again because the eighth field was on page four.

    83% automatable · 5 weeks to production

  • Manual data entry

    operations

    Copy from a tab, paste into a form. It is the single most common answer to “what takes the longest”, and the least often measured.

    81% automatable · 3 weeks to production

  • CRM updates

    sales

    The CRM is accurate on the last day of the quarter and fiction for the other eighty-nine.

    85% automatable · 2 weeks to production

  • Repetitive approvals

    operations

    A manager receives a request with no context, opens three systems to build that context, and then clicks Approve.

    68% automatable · 4 weeks to production

  • Internal knowledge discovery

    operations

    Asking in Slack, waiting, being sent a link to a document that was superseded in March.

    74% automatable · 3 weeks to production

  • Data reconciliation

    finance

    Two exports, a lookup formula, and an afternoon spent confirming that 96% of the rows match.

    89% automatable · 4 weeks to production

  • Meeting follow-ups

    sales

    Notes in a notebook, actions in someone's memory, follow-up on Thursday.

    79% automatable · 2 weeks to production

Twelve processes, and the average business we assess is losing 29 hrs a week across a handful of them. The audit's job is to find which handful, in yours.

The solution

Novaryn turns those processes into systems that run

Not assistants that help someone do the work faster. Systems that do the work, inside your existing stack, with a person on the decisions that need one.

  • It reaches your systems

    An agent that cannot write to your CRM has not automated anything — it has drafted something. Novaryn agents hold scoped, audited credentials to the systems of record, so the work finishes where the work lives.

    Not a chat window that produces text you then paste somewhere.

  • It knows what your business knows

    Retrieval runs over your own documents, tickets and wikis, permission-aware and with citations. When it does not know, it says so and escalates rather than inventing a policy that sounds plausible.

    Not a general model guessing at your refund terms.

  • A human holds the risky end

    Risk is a property of the action, not of the model's confidence. Irreversible, high-value, bulk and externally-visible actions are gated before execution — because a model that is certain it should issue a refund is exactly the case the gate exists for.

    Not autonomy as a marketing claim and a support incident as the result.

  • Everything is measured

    Every run records its tokens, cost, latency, tool calls and whether a human had to step in. You can answer “is this working and what is it costing” from a dashboard rather than from a feeling.

    Not a pilot that nobody can evaluate and nobody will cancel.

AI Opportunity Scanner

Find out what your business could automate

Move the controls. The score, the ranking and every rupee below are computed in your browser by the same engine that scores a real audit — there is no lookup table and no placeholder.

Your business

The real audit asks about thirteen dimensions, including the systems you run and which processes are manual today. This preview assumes a common stack and looks across every department.

AI Automation Score

59/ 100

Emerging

Hours saved / week
155 hrs
Full-time equivalent
3.9
Annual saving
₹60.2L
Payback
2.6 mo
Opportunity density
43% ×45
Systems readiness
100% ×30
Process clarity
0% ×15
Headroom
100% ×10

Real, targeted automation potential. The constraint is definition — a short discovery pass would sharpen these numbers considerably.

Top opportunities

  • Customer support₹9.9L / yr33 hrs / wk · 55% automatable4.2× · 2.9 mo
  • Data reconciliation₹8.2L / yr16 hrs / wk · 62% automatable4.3× · 2.8 mo
  • Email processing₹8.1L / yr22 hrs / wk · 66% automatable16.3× · 0.7 mo
  • Internal knowledge discovery₹7.6L / yr20 hrs / wk · 56% automatable10.1× · 1.2 mo
Run the full auditThirteen questions · four minutes · a report you keep

AI employees

Not tools. Roles.

An AI employee is an agent configured for a job — with a charter, the systems it needs, the processes it owns, and a written list of what it may never do without a person.

  • AI Sales Employee

    balanced

    Qualifies every lead before a rep opens it

    Owns the top of the funnel. Reads every inbound enquiry, researches the company, scores it against your criteria, updates the CRM and books the meeting — escalating anything above your value threshold to a human immediately.

    Owns

    • Lead qualification
    • CRM updates
    • Meeting follow-ups

    Never unattended

    Discounting · Contractual commitments · Outbound to a named-account list

    What it does, step by step

  • AI Support Employee

    balanced

    Answers what it knows, escalates what it doesn't

    Handles first-line support from your own documentation. Answers with citations, classifies and tags every ticket, detects when a customer is losing patience, and hands over with a summary rather than a transcript.

    Owns

    • Customer support

    Never unattended

    Refunds · Account deletion · Public statements about an incident

    What it does, step by step

  • AI Finance Employee

    deep

    Reads every invoice, reconciles every ledger

    Owns the paperwork half of finance. Extracts invoice data, matches it against purchase orders, codes expenses, reconciles systems that should agree, and puts only the exceptions in front of a person.

    Owns

    • Invoice processing
    • Data reconciliation

    Never unattended

    Payment execution · Vendor bank detail changes · Ledger adjustments

    What it does, step by step

  • AI Operations Employee

    balanced

    Keeps the systems in agreement

    The generalist. Processes documents and spreadsheets, moves data between systems, watches workflows for anomalies, prepares the daily summary and raises the alert before anyone notices the problem.

    Owns

    • Email processing
    • Document processing
    • Manual data entry
    • Repetitive approvals

    Never unattended

    Bulk deletion · Schema changes · Anything touching production credentials

    What it does, step by step

  • AI Research Employee

    deep

    Reads everything, cites its sources

    Answers questions that require reading. Searches your documents and the public web, compares competitors, produces research memos, and monitors topics you care about — always with the source attached.

    Owns

    • Internal knowledge discovery

    Never unattended

    Publishing externally · Representing a finding as a company position

    What it does, step by step

  • AI Reporting Employee

    deep

    The weekly report, written before Monday

    Owns recurring reporting end to end. Pulls from every source, reconciles the figures that disagree, writes the commentary, flags the anomaly you would have missed, and delivers on schedule.

    Owns

    • Reporting

    Never unattended

    Distribution to investors or regulators

    What it does, step by step

How it works

Six steps, and you can stop after the first

The audit stands alone. If the numbers do not justify a build, you have a report that says so and you have lost a fortnight rather than a quarter.

  1. Discover

    The business describes how it actually runs — volumes, systems, departments, bottlenecks. Scored, not guessed.

    Deliverable — Completed assessment + AI Automation Score

  2. Analyse

    Each manual process becomes a line item with hours saved, automation potential, difficulty, ROI and a priority.

    Deliverable — Ranked, costed automation opportunities

  3. Build

    The agents, AI employees and workflows the proposal described are configured against the customer's own knowledge.

    Deliverable — Configured agents and workflows

  4. Integrate

    The customer's existing systems are connected. Nothing is automated that cannot reach the system of record.

    Deliverable — Live, health-checked connections

  5. Deploy

    Promoted from staging once evaluations pass. Risk thresholds decide what runs unattended and what waits for a human.

    Deliverable — A production environment with approval policy

  6. Optimise

    Prompts, models and routing are tuned against evaluation datasets, and the change is measured rather than asserted.

    Deliverable — Measured version-over-version improvement

Integrations

Connected to the systems you already run

Agents act inside your stack rather than beside it. 18 connectors in production today, plus any REST API and any MCP server.

Communication

  • Gmail

    live

    Read, classify, draft and send from a shared or personal mailbox.

    oauth2 · webhooks

  • Outlook

    live

    The same mailbox operations across Microsoft 365 tenants.

    oauth2 · webhooks

  • Slack

    live

    Where approvals are requested and alerts land.

    oauth2 · webhooks

  • Microsoft Teams

    beta

    Approvals and alerts for Microsoft-first organisations.

    oauth2 · webhooks

  • WhatsApp Business

    beta

    The channel most Indian customers actually reply on.

    api key · webhooks

CRM

  • Salesforce

    live

    Read and write leads, opportunities and activity history.

    oauth2 · webhooks

  • HubSpot

    live

    Contacts, deals, pipelines and notes.

    oauth2 · webhooks

  • Zoho CRM

    beta

    Full CRM read/write for Zoho-first businesses.

    oauth2 · webhooks

Productivity

  • Google Drive

    live

    The document corpus most knowledge bases are actually built from.

    oauth2 · webhooks

  • OneDrive

    beta

    SharePoint and OneDrive document ingestion.

    oauth2 · webhooks

  • Notion

    live

    Internal wiki as a first-class knowledge source.

    oauth2

  • Google Calendar

    live

    Booking, availability and meeting context.

    oauth2 · webhooks

  • Google Sheets

    live

    The system of record nobody admits to having.

    oauth2

  • Confluence

    planned

    Space and page ingestion for the internal wiki.

    api key

Development

  • GitHub

    live

    Issues, pull requests and repository context.

    oauth2 · webhooks

  • GitLab

    planned

    The same, for GitLab estates.

    oauth2 · webhooks

  • Jira

    live

    Ticket creation, transition and search.

    oauth2 · webhooks

  • Zendesk

    live

    Helpdesk tickets, macros and satisfaction data.

    api key · webhooks

Databases

  • PostgreSQL

    live

    Read-only or scoped-write access to your own database.

    connection string

  • MySQL

    live

    The same, for MySQL and MariaDB.

    connection string

  • MongoDB

    beta

    Collection queries and aggregation pipelines.

    connection string

Commerce

  • Shopify

    beta

    Orders, customers, products and fulfilment status.

    oauth2 · webhooks

APIs & custom

  • REST API

    live

    Any HTTP API, described once and exposed to agents as typed tools.

    api key · webhooks

  • MCP servers

    live

    Connect any Model Context Protocol server; agents discover the tools they are permitted.

    mcp

  • Inbound webhooks

    live

    Any system that can POST becomes a workflow trigger.

    webhook · webhooks

  • S3-compatible storage

    live

    Bucket ingestion for document pipelines.

    api key

Missing one? Custom REST and MCP connectors are part of every build, not an add-on.

Industries

The same twelve processes, weighted differently

Every business has an inbox and a spreadsheet. What changes by sector is which of them is expensive — and what a regulator will let you automate.

  • Marketing & Media

    Campaigns, clients and reporting at volume

    Agencies run on client reporting, brief turnaround and inbox throughput. The work is genuinely creative for about a third of the week; the rest is assembling numbers other systems already hold.

    • Reporting
    • Email processing
    • Lead qualification
    • Internal knowledge discovery

    Client-confidential material must not cross account boundaries

  • Automotive

    Dealerships, service desks and parts

    Enquiries arrive across phone, WhatsApp and portals; service scheduling and parts availability live in different systems, and someone reconciles them by hand every morning.

    • Lead qualification
    • CRM updates
    • Customer support
    • Data reconciliation

    Dealer management systems are often on-premise with limited APIs

  • Insurance

    Claims, policies and underwriting evidence

    Claims and underwriting are document pipelines wearing a business suit. Most of the cycle time is reading, extracting and cross-checking paperwork against a policy.

    • Document processing
    • Repetitive approvals
    • Data reconciliation
    • Customer support

    Regulated decisioning — every automated recommendation needs a recorded human decision · Audit trail retention obligations

  • Financial Services

    Onboarding, reconciliation and reporting

    KYC packs, statement reconciliation and regulatory reporting consume analyst time that the firm hired for judgement, not for transcription.

    • Data reconciliation
    • Document processing
    • Reporting
    • Repetitive approvals

    Data residency and retention rules · Model output cannot be the sole basis of a customer-facing financial decision

  • Healthcare

    Intake, records and coordination

    Patient intake, referrals and insurance coordination are handled through forms and phone calls that never reach the record system in a structured form.

    • Document processing
    • Customer support
    • Manual data entry
    • Repetitive approvals

    Patient data requires strict access control and de-identification in prompts · Clinical decisions are never automated — assistive only

  • Real Estate

    Enquiries, listings and site visits

    Enquiry volume is high and qualification is shallow; most of a broker's day is deciding which of forty messages is worth a call back.

    • Lead qualification
    • Email processing
    • CRM updates
    • Document processing

    Listing data is frequently duplicated across portals

  • Logistics

    Shipments, exceptions and proof of delivery

    The happy path is already automated. The cost is in exceptions — a delayed shipment produces a dozen emails and three system updates, all by hand.

    • Customer support
    • Data reconciliation
    • Document processing
    • Reporting

    Partner systems vary in quality; retries and idempotency are mandatory

  • Manufacturing

    Orders, suppliers and quality records

    Purchase orders, supplier correspondence and quality documentation move between ERP, email and spreadsheets, and the spreadsheet is the one everyone trusts.

    • Manual data entry
    • Document processing
    • Reporting
    • Repetitive approvals

    ERP write access is usually the hardest integration in the estate

  • Professional Services

    Proposals, engagements and billing

    Billable people spend non-billable hours on proposals, status reports and timesheet reconciliation. The margin is sitting in the admin.

    • Reporting
    • Document processing
    • Internal knowledge discovery
    • Invoice processing

    Client confidentiality boundaries between engagements

  • SaaS

    Pipeline, support and product signals

    Inbound volume outpaces the team long before revenue does. Support tiering, lead routing and CRM hygiene are the first things to break.

    • Customer support
    • Lead qualification
    • CRM updates
    • Reporting

    Product telemetry and CRM disagree; one has to be made authoritative

Worked examples

What the numbers look like on a real business

Three operating profiles, each run through the same engine your own audit uses. The figures below are the model's output for those inputs — not testimonials, and not rounded up for the page.

  • B2B SaaS platform

    SaaS · 60 employees

    Support volume grew faster than the team. Two thirds of tickets were the same handful of questions, and the CRM was accurate only in the week before a board meeting.

    First project

    Support triage first — highest volume, existing documentation to retrieve from, and a failure mode that is a slower reply rather than a wrong transaction.

    Email processing — 24 hrs a week, live in 2 weeks, payback in 0.7 months.

    Automation score
    80/ 100
    Hours saved / week
    198 hrs
    Annual saving
    ₹71L
    To build
    ₹11.2L
    First-year return
    6.4×
    Payback
    1.9 mo

  • General insurance intermediary

    Insurance · 180 employees

    Claims and underwriting were document pipelines run by hand. Cycle time was dominated by reading paperwork and cross-checking it against a policy, not by the decision itself.

    First project

    Document extraction, gated. Every automated finding is presented to an underwriter with the page and clause cited — the decision stays human because the regulator requires it to.

    Email processing — 94 hrs a week, live in 2 weeks, payback in 0.2 months.

    Automation score
    79/ 100
    Hours saved / week
    670 hrs
    Annual saving
    ₹2.6Cr
    To build
    ₹13.2L
    First-year return
    19.9×
    Payback
    0.6 mo

  • Multi-branch automotive dealership

    Automotive · 95 employees

    Enquiries arrived on WhatsApp, phone and three portals. Nobody could say how many leads were never followed up, because there was no single place they all landed.

    First project

    Lead qualification and CRM hygiene together — the second is what makes the first measurable, and without it the improvement is invisible to management.

    Lead qualification — 108 hrs a week, live in 3 weeks, payback in 0.2 months.

    Automation score
    76/ 100
    Hours saved / week
    319 hrs
    Annual saving
    ₹1.3Cr
    To build
    ₹11.2L
    First-year return
    11.9×
    Payback
    1 mo

These are modelled outcomes, not customer results. Novaryn is early and has no published engagements yet — rather than dress up invented ones, we ran three realistic business profiles through the production scoring engine and printed what it returned. Run your own and you will see the same arithmetic applied to your answers.

What it is worth

The return, before you talk to anyone

Three inputs. The figure below is produced by the same engine that scores a paid audit — not by a formula written to make the number look good.

Volumes are estimated from headcount. The full audit asks for your real ones, which usually moves the figure in both directions — up on throughput, down where a process is already partly automated.

Hours removed / week
331 hrs
Full-time equivalent
8.3
Annual saving
₹1.2Cr
To build
₹14.9L
First-year net
₹1.1Cr
Payback
1.4 months

Where it comes from

  • Customer support60 hrs/wk · ₹22.5L/yr
  • Email processing44 hrs/wk · ₹16.3L/yr
  • Internal knowledge discovery41 hrs/wk · ₹15.2L/yr
  • Manual data entry35 hrs/wk · ₹13.1L/yr
  • Data reconciliation33 hrs/wk · ₹12.2L/yr

This assumes nothing is automated today and that every listed system can be connected. It excludes change management, the cost of your team's time during implementation, and any process the audit would find is already partly handled. Automation potential is capped below 100% for every process — something always needs a person.

Get the version with your numbersFour minutes · no call

Pricing

Priced by what you get, not by seats

Start with the audit. Every rupee of it is credited against whatever you build next, so the worst case is that you paid for a report that told you not to bother.

  • 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

Evidence

We run 2 AI products of our own

Not a portfolio page — the reason to believe the rest of this one. Every product below is live, built on this platform, and open in a new tab right now.

Next

Find out what your business could automate

Thirteen questions, four minutes, and a costed opportunity list you keep whether or not you build anything with us.

Start your AI auditTalk to an engineer instead