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About

Sigzen AI is the AI Visibility & Automation Studio of Sigzen Technologies Pvt Ltd, a technology company that has implemented and supported business systems since 2015. We measure before we promise, publish our method and prices, and tie fees to outcomes where we can.

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A studio inside a company that builds systems.

Sigzen AI exists because buyers changed where they ask. When a marketing lead wants a shortlist or an operations head wants a supplier, the question now goes to ChatGPT, Gemini, Perplexity or Google AI, and the answer is the shortlist. Most brands are not in it and cannot see why. Sigzen Technologies Pvt Ltd has implemented and supported business systems since 2015. The studio was set up to apply that same discipline, measured work on real systems, to a newer problem.

The studio does two things. The first is AI visibility: measuring how often you are named or cited across five engines, fixing what the engines read on your site, earning the citations they trust off-site, and correcting what they get wrong about you. The second is AI automation: agents built on the systems you already run, so the leads, enquiries and documents that follow are handled without adding headcount. Visibility is the front door. Automation is what we build once we are inside.

We are held to account in public. Our own share of answer on 20 buyer prompts is published and refreshed every week, losses included. Our method is published with a version number, so you can check it and so can the engines. Our prices are published, so a first call starts with fit rather than a quote. If we cannot get ourselves cited, you should not hire us.

What we hold ourselves to.

  • 01

    Measure before we promise

    Every engagement starts with a baseline on your own prompts. If your share of answer is already fine, we say so and you keep the report.

  • 02

    Publish the method

    The playbooks page describes how we measure, how we optimise and what we refuse to do, with a version number and a changelog. A method you cannot read is not a method.

  • 03

    Publish the price

    Audit, programme and sprint prices are on the site in two currencies and are the same for everyone. It filters out the wrong calls and spares the right ones a negotiation.

  • 04

    A person sends

    Our outreach engine researches and drafts; a human reads, edits and sends, inside each platform's rules. The same applies to community posts, review invitations and press pitches.

  • 05

    Official APIs only

    We measure engines through their official APIs and build automation on documented integrations. No scraping, no unofficial access, no shortcuts that break the day a platform changes its terms.

How we work.

  • 01

    Diagnose, then sprint, then run

    A paid diagnosis gives you the baseline and the three fixes that matter most. A fixed-scope sprint delivers them. A monthly programme keeps the number moving. Each rung is a separate decision, and the audit is credited against a sprint booked within 30 days.

  • 02

    Fixed scope and acceptance criteria

    Every statement of work names its deliverables, its outcome metric and what finished means before anything starts. Changes in scope go to a change order or to the next rung. They are not absorbed quietly and billed later.

  • 03

    One dashboard

    One reporting format for everything: share of answer by engine, citations gained, errors corrected, hours saved, updated weekly. No bespoke decks and no numbers you cannot trace back to a prompt or a process.

  • 04

    Case studies, with your sign-off

    Case-study and before-and-after rights are a default clause in our agreement, so results can be shared and the next client can check them. Nothing is published without the client's written sign-off on the final text and numbers.

How we write Insights.

  • 01

    Sources first

    Every statistic in an article links to the primary source that published it, with the data period and the country when it is not global. A number we cannot read at its source does not appear.

  • 02

    Drafted with AI, checked by people

    Articles are drafted with AI from sources the editorial team selects. A person then checks every number against its source and edits the whole piece before it is published. Each article says so at the end.

  • 03

    Real dates

    The published date is the day an article went live. The updated date changes only when the substance does: new data, a corrected claim, a changed engine. We never re-date a page to make it look fresh.

  • 04

    Corrections in the open

    When we get something wrong, the article gets a dated correction note at the top saying what changed. Tell us at the email address in the footer and we will check it against the source.

  • 05

    Our interest, declared

    We sell AI visibility and automation work. Articles about prices or tactics say so, and our own prices are shown separately and never counted in a benchmark. Examples marked illustrative are ours, with invented brands.

Company facts

Parent company
Sigzen Technologies Pvt Ltd
Founded
2015
Certifications
ISO 27001 and ISO 9001
Based in
India, working with clients worldwide
Methodology version
1.0

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