ai development

Sahaj

Transform complex data challenges into streamlined business outcomes using artisanal software engineering, AI, and machine learning for data-led organizations.

Paid only

Price not published

Sahaj screenshot

About Sahaj

Sahaj is an artisanal technology services firm dedicated to solving complex business problems through custom-built software solutions. By integrating advanced fields like Artificial Intelligence, Machine Learning, and Data Engineering, the company helps organizations navigate digital transformation. Their approach is rooted in the Sanskrit meaning of their name—simplicity—aiming to create natural and innate technical architectures that provide a competitive edge without unnecessary complexity. The firm positions itself as a collective of innovators who prioritize the pursuit of brilliance over traditional corporate structures, focusing on delivering high-impact technological outcomes. The firm operates through a unique execution methodology characterized by first-principles thinking. This involves questioning fundamental assumptions to avoid technology force-fits and ensuring that every solution is purpose-built for the client's specific needs rather than relying on generic templates. They utilize lean, cohesive teams that function without traditional hierarchy, which encourages faster feedback loops and more effective collaboration between the firm and its partners. Their core focus areas are intentionally broad yet deep, spanning from strategic advisory roles to the complex, full-scale development of data platforms and specialized AI models. This service is ideal for mid-to-large scale organizations that require more than off-the-shelf software to handle their increasingly complex data workloads. It specifically caters to technical leaders, data scientists, and business executives in industries such as finance, logistics, and retail who are looking to unlock the latent value in their existing data assets. Whether a company needs to overhaul its entire platform engineering stack or deploy highly sophisticated machine learning models for predictive analytics, the firm provides the high-level expertise required for such specialized and high-stakes transitions. What distinguishes Sahaj from standard consultancies is its unwavering commitment to client enablement and the artisanal nature of its craftsmanship. Unlike traditional firms that often create long-term dependencies through proprietary black-box systems, Sahaj focuses on full knowledge transfer to ensure clients can manage and evolve their systems independently once the engagement ends. Their value system—based on trust, respect, curiosity, and craftsmanship—results in a distinct fingerprint on every project, prioritizing elegant and simple solutions that ensure high adoption rates and long-term organizational success.

Sahaj pros & cons

Pros

  • Employs first-principles thinking to avoid mismatched technology solutions.
  • Focuses on full knowledge transfer to prevent long-term client dependency.
  • Utilizes lean, non-hierarchical teams for faster feedback and execution.
  • Global presence with offices in major tech hubs like Austin, London, and Singapore.
  • Combines software engineering with deep expertise in AI and ML.

Cons

  • Does not offer standardized off-the-shelf products for immediate deployment.
  • Service-based model requires significant time investment from client teams.
  • Lack of transparent public pricing makes initial budgeting difficult.
  • Lean team model might challenge clients accustomed to traditional corporate hierarchies.

Sahaj use cases

  • Data engineering leads can partner with Sahaj to modernize legacy platforms into scalable, AI-ready data architectures.
  • Business executives seeking digital transformation can utilize their advisory services to identify purpose-built solutions without technology bloat.
  • Product managers can leverage Sahaj's lean teams to prototype and deploy complex ML models through an iterative feedback process.
  • CTOs looking for long-term sustainability can engage Sahaj to build internal systems while receiving full knowledge transfer for their own teams.

Sahaj features

  • platform engineering
  • ai and machine learning implementation
  • custom artisanal software development
  • knowledge transfer and client enablement
  • lean team collaboration structure
  • first-principles advisory services
  • data engineering and architecture
  • purpose-built solution design

Sahaj pricing

Is Sahaj free? No, Sahaj doesn't offer a free plan.

Custom Solutions

Price varies

  • Purpose-built solutioning
  • AI & ML implementation
  • Data Engineering
  • Platform Engineering
  • Strategic Advisory
  • Full knowledge transfer
  • First-principles consulting
  • Lean team collaboration

Sahaj FAQs

What specific areas of technology does Sahaj focus on?

Sahaj specializes in Platform Engineering, Data Engineering, and AI/ML implementation. They combine these disciplines to create purpose-built solutions that drive data-led transformation and unlock the full potential of a client's data.

How does Sahaj ensure that clients are not dependent on them long-term?

The firm prioritizes client enablement by working in close partnership throughout the project. They ensure a full knowledge transfer so that the client's internal team has the skills and documentation to manage the systems independently.

What is the First Principles thinking approach used by the firm?

This approach involves asking fundamental questions and avoiding assumptions at the start of a project. It allows the team to find optimal, out-of-the-box solutions that address the root cause of a problem without forcing unnecessary technology.

Does Sahaj have a global presence for international projects?

Yes, Sahaj has a significant global footprint with offices in the United States, United Kingdom, India, Australia, and Singapore. This allows them to support international clients across different time zones and regional markets.

How does the team structure differ from traditional consulting firms?

Sahaj uses lean, cohesive teams with no internal roles or hierarchy. This structure is designed to drive sharper focus, enable more effective collaboration, and ensure that feedback is incorporated early and often.

Open roles

All AI jobs

Data Scientist

Benefits:

  • Unlimited leaves

  • Life insurance & private health insurance

  • Stock options

  • No hierarchy

  • Open Salaries

Education Requirements:

  • PhD, Master’s, or Graduate Degree in Computer Science

  • Degree in Machine Learning or AI

  • Degree in Operational Research

  • Degree in Statistics or Mathematics

Experience Requirements:

  • Proven track record in client interaction

  • Experience collaborating with engineering and business teams

  • Expertise in formulation, solving and deploying Data Science models

  • Expertise in problem solving while being hands on

Other Requirements:

  • Conversant with end-to-end data science model life cycle

  • Conversant with at least 2 areas: NLP, CV, RAG, LLMs, or ML

  • Proficiency in Python and relevant libraries

  • Theoretical strength in deep learning and conventional machine learning

Responsibilities:

  • Conceptualizing, formulating, coding and deploying solutions

  • Interacting with clients to make sense of ambiguous problem statements

  • Building systems like RAG, Multiagent, or LLM-based solutions

  • Solving problems in computer vision, speech, or NLP

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Data Engineer

Benefits:

  • Unlimited leaves

  • Life insurance & private health insurance

  • Stock options

  • No hierarchy

  • Open Salaries

Experience Requirements:

  • Demonstrated experience as a Senior Data Engineer

  • Experience with Python or functional languages like Scala

  • Design and development of big data applications using Databricks or Spark

  • Building data products by integrating large sets of internal/external data

Other Requirements:

  • Nuanced understanding of code quality and Test Driven Development

  • Understanding of Cloud platforms, DevOps, GitOps, and Containers

  • Ability to deliver applications end-to-end using CI/CD

Responsibilities:

  • Collaborate with Data Scientists to deliver AI and ML systems

  • Build frameworks and tooling for complex data ingestion

  • Consult clients on data strategy and modernizing infrastructure

  • Model data for increased visibility and performance

  • Work in short sprints to deliver working software

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