Build, Grow, & Scale Your Vision

Strategy, marketing, and operations expertise to drive your project success.

Who We Are

We are Shard Works - tech veterans helping founders build, grow, and scale through strategy, marketing, and operations.

What We Do

Core Services

A simple, effective approach to deliver excellence.

Product Strategy

From concept to execution, we help define your product vision, roadmap, and go-to-market strategy with Web3-native thinking

On Call..

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Present

AI Developer

Sales expert

Marketing expert

You

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AI Developer

Sales expert

Marketing expert

You

AI Developer

Sales expert

Marketing expert

You

Marketing & Community

Build engaged communities and effective growth strategies tailored to decentralized ecosystems and web3 natives.

Filters :

Work Efficiency

Cost Reduction

Automated Tasks

Lead Nurturing

Work Efficiency

+23%

Day 1

Day 2

Day 3

Day 4

Day 5

Day 6

Day 7

Work efficiency in this week increased to 23% as compared to last week.

Overall :

48.9%

Overall now you have 48.9% better system as compared to previous week

Export

Work Efficiency

+23%

Day 1

Day 2

Day 3

Day 4

Day 5

Day 6

Day 7

Work efficiency in this week increased to 23% as compared to last week.

Work Efficiency

+23%

Day 1

Day 2

Day 3

Day 4

Day 5

Day 6

Day 7

Work efficiency in this week increased to 23% as compared to last week.

People Operations

Build resilient, high-performing organizations through strategic people policies tailored for decentralized and distributed teams.

class Sampling(layers.Layer):

    """Uses (mean, log_var) to sample z, the vector encoding a digit."""

 

    def call(self, inputs):

        mean, log_var = inputs

        batch = tf.shape(mean)[0]

        dim = tf.shape(mean)[1]

        return mean + tf.exp(0.5 * log_var) * epsilon

class Sampling(layers.Layer):

    """Uses (mean, log_var) to sample z, the vector encoding a digit."""

 

    def call(self, inputs):

        mean, log_var = inputs

        batch = tf.shape(mean)[0]

        dim = tf.shape(mean)[1]

        return mean + tf.exp(0.5 * log_var) * epsilon

class Sampling(layers.Layer):

    """Uses (mean, log_var) to sample z, the vector encoding a digit."""

 

    def call(self, inputs):

        mean, log_var = inputs

        batch = tf.shape(mean)[0]

        dim = tf.shape(mean)[1]

        return mean + tf.exp(0.5 * log_var) * epsilon

Custom Solutions

Bespoke consulting and solutions for your organization's unique challenges at any stage of development.

Why Choose Us

Maximize efficiency and impact

Get what you need quickly

Proven Web3 Expertise

Our team brings hands-on experience from leading crypto projects and business giants, with a track record of success in both corporate and start-up environments.

Domain Specialist Network

Access our curated network of specialists across product, community building, and technical implementation - all coordinated through a single point of contact.

Solution-Focused Approach

We deliver actionable strategies and implementation support, not theoretical frameworks. Our solutions are practical, measurable, and tailored to your resources.

Where We Are From

Our Team's Experience

Our experts have worked at leading companies across Web2 and Web3

Contacts

Ask whatever you have in your mind

Ask whatever you have in your mind

Whether you have questions or are ready to discuss your business, we’re here to help. Reach out today.

Whether you have questions or are ready to discuss your business, we’re here to help. Reach out today.

gm@shard.works

Shard Works

Your personal digital product consultant, helping you build, grow and scale your vision!

© All right reserved

© All right reserved