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Proof

Built and trusted since 2018

Projects delivered
680+
Happy clients
310+
Countries served
25+
Client retention
98%
Certified engineers
20+

Trusted by teams we have built for

  • Aralia
  • Rosa Pistrina
  • Lashbo
  • Micromunchi
  • Ndessi Finance
  • Payroll Ninja
  • POD
  • Petdx
  • Yokey
  • Spin Up
  • Starwear
  • Udlins
  • Vegpal
  • Wander Wings
  • Wish It
  • Wisl

Official partners

Certified partners on the platforms we build on.

  • SnowflakePartner
  • DatabricksPartner
  • MicrosoftPartner

Who we are

We are a team of data scientists and engineers in India, Germany, France and Bahrain who take data and AI from first question to production — and keep it running.

Why it matters

Most AI projects stall on the data, not the model

What independent research says, and why we start every engagement with your data.

Third-party research, quoted as published. Predictions are the source's forecasts, not measured results.

Use cases

What problem are you solving?

Start from the problem, not the technology: six things teams most often ask us to build.

Capabilities

What we do

    • Snowflake
    • Databricks
    • Microsoft Fabric
    • Microsoft Azure
    • dbt
    • Apache Airflow
    • Apache Kafka
    • Apache Spark

    Data Engineering

    Pipelines and warehouses that deliver clean data on time.

    • Python
    • Databricks
    • Apache Spark
    • Microsoft Azure
    • Google Cloud

    Data Science & ML

    Forecasting, recommendation and anomaly models, evaluated before they ship.

    • Power BI
    • Microsoft Fabric
    • Snowflake
    • SQL Server
    • PostgreSQL

    Analytics & BI

    Trusted KPIs and dashboards your teams actually open.

Our data stack

From raw data to decisions

  1. 01 · Sources

    • ERP
    • CRM
    • SQL databases
    • SaaS APIs
    • Files & events
  2. 02 · Ingest

  3. 03 · Store

  4. 04 · Transform

  5. 05 · Serve

  6. 06 · AI

Stage 03 · Store

Snowflake

  • Official Snowflake partner

Design, build, migrate and optimize Snowflake with an official Snowflake partner.

Explore Snowflake services

What we deliver

  • Snowflake Data Warehouse Design and Implementation
  • Snowflake Data Pipelines and ELT Development
  • Snowflake Cost Optimization and Resource Management
  • SQL Server to Snowflake Migration
  • Snowflake Architecture and Performance Optimization
  • Snowflake SQL Development and Query Tuning
  • Snowflake Security, RBAC, and Data Governance
  • Snowflake and Databricks Platform Optimization
+6 more services

Showcases

What we build with data

The kinds of systems our data science team builds, and how we measure them. Charts are illustrative.

  1. Retail and FMCG

    Demand forecasting

    Problem
    Forecasts built per team don't agree. Planning needs one forecast for SKU, store and region.
    Approach
    Gradient-boosted models on price, promotion and weather, reconciled so every level adds up.
    We measure
    Error, bias and skill against a seasonal baseline.
    • Python
    • LightGBM
    • Prophet
    • statsforecast
    • dbt
    • Airflow
    • Databricks
    Illustrative History, then a forecast with its range
  2. Subscription and Telecom

    Customer churn prediction

    Problem
    Retention teams need to know who will leave, and why, early enough to act.
    Approach
    Calibrated models on usage and billing, with a reason behind every score.
    We measure
    Precision in the top decile, on a holdout.
    • Python
    • scikit-learn
    • XGBoost
    • SHAP
    • dbt
    • Snowflake
    • MLflow
    Illustrative Ranked by risk; the top group highlighted
  3. Manufacturing

    Predictive maintenance

    Problem
    Downtime is expensive and fixed schedules waste good parts. Teams need warnings days ahead.
    Approach
    Sensor features feed a remaining-life model and an anomaly score per machine.
    We measure
    Warning lead time and false alarms per machine.
    • Python
    • PyTorch
    • scikit-learn
    • tsfresh
    • Kafka
    • TimescaleDB
    • Grafana
    Illustrative A signal drifting past its alert threshold
  4. Fintech

    Fraud and anomaly detection

    Problem
    Rules miss new fraud, and every false alarm blocks a real customer.
    Approach
    Known-pattern models plus anomaly detection for new ones, scored in real time.
    We measure
    Recall at a fixed false-alarm rate, and latency.
    • Python
    • LightGBM
    • PyOD
    • NetworkX
    • Kafka
    • Feast
    • Redis
    • FastAPI
    Illustrative Two normal clusters and a few outliers
  5. Insurance and Legal

    Document intelligence with LLMs

    Problem
    Specialists spend hours pulling the same fields from claims, contracts and scans.
    Approach
    OCR plus LLM extraction to a fixed format, each field linked to its source.
    We measure
    Field accuracy and how many documents need a person.
    • Python
    • LlamaIndex
    • OpenAI or open-weight LLMs
    • pgvector
    • Azure Document Intelligence
    • FastAPI
    Illustrative Fields extracted into a structured record
  6. Manufacturing

    Computer-vision quality inspection

    Problem
    Manual inspection is slow, varies by shift and misses rare defects.
    Approach
    Detection models trained on images from your line, running at line speed.
    We measure
    Recall per defect type at an agreed reject rate.
    • Python
    • PyTorch
    • Ultralytics YOLO
    • OpenCV
    • Label Studio
    • ONNX Runtime
    • NVIDIA Jetson
    Illustrative Parts on a line; one flagged as defective

Recent work

Products we have shipped

See the full portfolio

Responsible AI

How we build AI responsibly

Practices we follow on every model we ship.

Responsible AI is part of how we deliver, not a separate checklist. These practices shape how we scope, test and run every model, and we are happy to walk you through how they apply to your project.

  • ISO 27001 certified
  • GDPR-compliant
  • NDA on request
  • Measured before it ships

    Every model is evaluated against metrics and a baseline agreed with you, before launch.

  • People stay in the loop

    High-impact outputs are reviewed by a person. You decide where automation stops.

  • Personal data protected

    PII is kept to a minimum, masked or kept out of prompts and training data where possible, under GDPR.

  • Explainable outputs

    Where it matters, scores and predictions come with reasons your teams can check (e.g. SHAP).

  • Monitored after launch

    Drift, quality and cost are tracked once a model is live, with retraining planned.

  • Ready for the EU AI Act

    Built with the Act's risk classification, documentation and transparency duties in mind.

Process

How we work

One way of working for data platforms, AI and the apps built on them: scoped first, built in short sprints, supported after launch.

Ways to engage

  • Fixed priceAgreed scope, one cost and a set timeline.
  • Dedicated teamEngineers who work inside your team, month to month.
  • Time & materialsPay for the hours used and reprioritise as you learn.
  • No lock-in: stop after any phase, with the work handed over.
  • Code, data and IP are yours.
Book a Meeting

Timelines are typical. Every engagement is scoped before it starts.

Start small, scale when it works

  1. Assessment1–2 weeks: your data, goals and a roadmap with a fixed estimate.
  2. Proof of conceptTypically 4–6 weeks on your real data, judged against agreed metrics.
  3. ProductionBuilt in sprints, launched, then monitored and improved.
  1. Step 01Typical duration: 1–2 weeks

    Discover & scope

    Workshops with your team and an audit of your current systems, data and apps. We agree the goals and how success will be measured.

    You get

    • Roadmap
    • Architecture outline
    • Fixed estimate
  2. Step 02Typical duration: 1–3 weeks

    Design & prototype

    Solution architecture, data model and UX flows, then a clickable prototype or a proof of concept running on your real data.

    You get

    • Technical blueprint
    • Data model
    • Validated prototype
  3. Step 03Typical duration: 2-week sprints

    Build in sprints

    A demo at the end of every sprint. CI/CD, automated tests and security are part of the build from day one, not added at the end.

    You get

    • Sprint demos
    • CI/CD and test suite
    • Security from day one
  4. Step 04Typical duration: 1–2 weeks

    Launch

    Performance and security checks, go-live on your cloud, then documentation and hands-on training for the people who will run it.

    You get

    • Production release
    • Runbooks and docs
    • Team training
  5. Step 05Typical duration: Ongoing

    Support & scale

    Monitoring, agreed SLAs and steady improvement: performance tuning, model retraining and new features as usage grows.

    You get

    • On-call engineers
    • SLA-backed support
    • Model retraining

Services

Everything we build

Data and AI first — and the apps, platforms and stores we've shipped for over a decade.

AI development

7 services

Generative AI, agents and chatbots built into your products and workflows.

What we build

  • Assistants and copilotsInside the tools your teams already use.
  • Document automationInvoices, contracts and forms processed.
  • AI agents for workflowsMulti-step tasks, with a human in the loop.
  • RAG search over your knowledgeAnswers grounded in your own documents.

Models and frameworks

  • Azure OpenAI
  • OpenAI
  • Anthropic Claude
  • LangChain
  • Python
Explore AI development

Product engineering

19 services

Mobile apps, websites and online stores, designed, built and shipped end to end.

Industries

Industries we serve

Pick an industry to see what we can build for it.

Healthcare

Clinical, operational and patient data brought together on platforms built with privacy and access control from day one. Forecasting, document AI and risk models that help care teams plan and act earlier.

  • Patient-flow forecasting

    Admissions, bed occupancy and staffing demand predicted days ahead, so rotas and capacity plans keep up.

  • Clinical document extraction

    Referrals, discharge notes and forms turned into structured, searchable data without staff retyping them.

  • Readmission risk

    Explainable risk scores that help care teams decide which patients to follow up with after discharge.

Typical data and stack

  • EHR / EMR
  • HL7 / FHIR
  • Azure
  • Databricks
  • Power BI

Why us

Why teams choose Equitysoft

What you can hold us to on every engagement, from the first call to the handover.

  • Official partner

    Official Snowflake, Databricks and Microsoft partners.

  • Data and product, one team

    From pipelines and models to the app your users open, built by one team.

  • Close to you

    Offices in Germany, France, Bahrain and India, across Europe, the Gulf and Asia.

  • Secure by default

    ISO 27001 certified and GDPR-compliant, with an NDA signed on request.

  • You own everything

    Code, data and IP are yours, from the first commit to the final handover.

  • No lock-in

    Every engagement is phased: stop after any phase, with everything handed over.

  • 680+ projects
  • 310+ clients
  • 98% client retention
  • 20+ certified engineers
  • since 2018
Talk to an engineer

Recognition

Trusted by industry leaders

Recognised globally for innovation, reliability and AI-driven excellence.

  • FindBestWebDevTop 10 Custom Software Development
  • TechreviewerTop iOS App Developers 2020
  • BusinessFirmsVerified
  • The ManifestMost Reviewed IT Services Companies, Dallas
  • DesignRushTop Mobile App Development Companies
  • ClutchTop IT Services, India 2023
  • UpworkTop Rated Plus
  • Fiverr

Testimonials

In their words

They had excellent communication skills, which helped meet the project timelines. Equitysoft Technologies Pvt Ltd met all the project timelines, which satisfied the client's needs. They communicated well, and their expertise impressed the client.

Winfred Antwi · Clutch review

01 / 10

Readiness check

How ready is your data for AI?

Five questions, two minutes. Get your level and the next three steps.

  • Your level, from Foundations to AI-ready
  • Three concrete next steps for your team
  • No email needed to see your result

Question 1 of 5

Where does your data live?

Pick the answer closest to where you are today.

Your answers stay in your browser unless you ask for a review.

FAQ

Questions buyers ask us

Straight answers on scope, ownership, security and how we work. Can't find yours? Ask us directly.

business@equitysoft.in
  • With a free consultation call, then a Discover & scope phase (1–2 weeks) with workshops and an audit. You get a roadmap, an architecture outline and a fixed estimate.

  • Yes. We sign an NDA on request before you share any details, so the first conversation can cover your real data and systems.

  • You do. Code, data and intellectual property are yours, and everything we build for you is handed over to your team.

  • No. Every engagement is phased: you can stop after any phase with the work handed over, or continue month to month with a dedicated team.

  • We are ISO 27001 certified and GDPR-compliant, and we sign NDAs on request. Personal data is kept to a minimum or masked wherever possible.

  • Snowflake, Databricks and Microsoft (Fabric, Azure, Power BI) as official partners, plus AWS, Google Cloud, dbt, Apache Airflow, Apache Kafka and Apache Spark.

  • Yes. With the dedicated team model our engineers work inside your team, month to month. Fixed price and time & materials are also available.

  • Yes. Mobile apps, web apps and e-commerce stores have been part of our work for over ten years, and they often sit on top of the data platforms we build.

Contact

Let's build your next data product

Tell us about your data or AI challenge. We reply within one business day.

  • NDA on request
  • Free consultation
Offices
  • Ahmedabad, India
  • Usingen, Germany
  • Gouesnach, France
  • Bahrain
Partners
  • Snowflake Partner
  • Databricks Partner
  • Microsoft Partner

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