Tachyon Knowledge — AI Consulting and Advisory Agency

AI consulting and advisory, built on data you can trust

We help organizations decide where AI belongs, build the data and cloud foundations beneath it, and put it to work responsibly. Independent research since 2010, now applied as AI advisory.

Book an AI advisory call How we work

What we do

AI advisory, from strategy down to the stack beneath it

Every engagement rests on four design principles, Modularity, Abstraction, Orchestration and Distribution, and on the Compute, Storage and Network that process, store and communicate DATA THE KING!

Design principles

ModularityAbstractionOrchestrationDistribution

AI Strategy and Readiness

Find where AI can help, rank use cases by value and risk, and check whether your data and your teams are ready.

Data Foundations

Data warehouse, data lake and data mesh with clear ownership and governance, so AI has trustworthy data to learn from.

Cloud and AI Architecture

Design and review AI solutions on AWS, Azure and Google Cloud: serverless, containers, generative AI and machine learning, built to scale and to cost what you expect.

Governance and Trust

Stakeholder permission, time-stamped changes and transparent data trails, so your AI rests on data that was changed legitimately.

Team Enablement

Hands-on workshops and train-the-trainer programs that leave your own people able to build, run and question AI.

Research and Quantum Readiness

Independent research on what comes next, from machine learning to quantum computing, and what it means for your roadmap.

Foundations

ComputeStorageNetwork

For processing, storing and communication of DATA THE KING!

How we work

From the first conversation to your own team running it

Listen. We map your decisions, your data and your constraints before we recommend anything.
Prioritise. We rank AI opportunities by value, risk and readiness, and agree what not to do.
Prove. We build a small pilot on your data to test the idea before you commit a budget.
Hand over. We train your team and document the design, so you are not dependent on us.

Our thinking

Why we start with data

Loss of essence happens in Natural (Data) to Digital (Data) transformation. If there is no loss of essence in mapping natural things to digital, we call it Godly Transformation.

The main actor here is data, that's why we call it King!

Data is King!

Its value, variety, velocity, veracity and volume keep changing. We call it Big Data, and the King has many incarnations.

If Data Processing is Computing then Big Data Processing may be called Cloud computing.
Processed Data may be called Information.
Processed information may be called Knowledge!
Processed knowledge may be called Intelligence!

We need to go beyond intelligence. Making machines intelligent is a step beyond it, and we make machines intelligent by making them learn by themselves: Machine Learning. This is where AI advisory begins.

Because data keeps changing, one question decides whether an AI system can be trusted: who is changing the data, and do its stakeholders know?

Illegitimate

If a Data is getting changed without its stakeholders knowledge then that change may be termed as illegitimate.

Legitimate

If data changes are time stamped with its all stakeholders permission then those changes may be termed as legitimate changes.

Public and private data are the two categories a well established human system may have. Bringing transparency to data transformation has been the desire of humankind from the day one of the data, and Blockchain, as of now, brings that transparency.

Trustworthy AI starts with transparent data.

FOUNDED 2010

Tachyon Knowledge

Tachyon Knowledge was founded in 2010 by a team of particle physicists, IP analysts, technology evangelists, and software architects, with the goal of pursuing the highest level of independent research in service sectors. Today we apply that research discipline as an AI consulting and advisory agency. Our mission is to help people build better things, faster, by bridging the gaps between a company's project needs and resource skill sets.

Our own stack

What we have built and run ourselves

Our advice comes from running real systems. This is an iterative record of how we moved our own application and website from legacy hosting to the current state of the art.

THE PROBLEM

Organizations and individuals make many spontaneous decisions, from which career to start with to which technology to adopt. Things could be much better if the decision were analysed first: with data as the key actor, better decisions come quicker.

OUR ANSWER

Tachyon Knowledge, with an idea of “Hear the Unheard and Know the Unknown”. Only ideas with a good intent, where DATA is the key actor. Modern work is infrastructure and DATA intensive, and how we access the infrastructure to process our DATA is one of the key differentiators.

Where we started

Infrastructure: In a VM on VMWare infrastructure at Co-Located Center!
S/W: VMWare/Linux/Apache/Mysql/php/Drupal LMS!

2011As it was only a research workload so there was no external traffic and no earning hence we started exploring OpenStack for Tachyon Knowledge as a private cloud but realised early that there may be better available options.
2012To make the LMS up and running 24*7, we migrated to shared hosting! Cost and security were two reasons we started exploring something better!
2018Finally after evaluating Azure, GCP and AWS we decided to migrate to Multi-Cloud-hybrid mode.
2022Serverless and Serverless Containers would be key contributors towards better user experience, we started investing in that direction!
2023Data Warehouse for Analysing structured data, (Operational) DynamoDB and (Analytical) Redshift!
2024Data Lake for structured and unstructured data with centralized governance!
2025Data Mesh for Decentralized governance!
2026vBASK - High-Level Architecture: AWS Edge Computing Architecture with DataMesh

Mocks: Botanical Garden Iris Classifier — Botanical Garden Iris Classifier

With supporters ranging from industries, universities and start-ups, Tachyon Knowledge has taken a different approach to technology research and learning. We pilot before we scale, because the best way to learn is by doing.

Talk to us about your AI roadmap

Tell us what you are trying to decide, and we will suggest where to start.