Forecast demand
Forecasts by product, store and region that planning can trust.
- Python
- Databricks
- Snowflake
- MLflow
Data & AI engineering since 2018
From raw data to products people use.
Use cases
Start from the problem, not the technology: six things teams most often ask us to build.
Forecasts by product, store and region that planning can trust.
Churn scores with the reason behind each one, early enough to act.
Extract, check and route invoices, contracts and forms with LLMs.
Anomaly and vision models that flag issues as they happen.
A governed warehouse and dashboards every team agrees on.
dbtAssistants, search and recommendations inside your app.
Capabilities
Data science, data analytics, data engineering and AI agents, designed, built and run by one team.
Microsoft Fabric
dbtPipelines and warehouses that deliver clean data on time.
Forecasting, recommendation and anomaly models, evaluated before they ship.
Microsoft Fabric
dbtTrusted KPIs and dashboards your teams actually open.
Generative AI, agents and chatbots built into your products and workflows.
Mobile apps, websites and online stores, designed and shipped end to end.
Why it matters
What independent research says, and why we start every engagement with your data.
60%
of AI projects without AI-ready data will be abandoned through 2026.
63%
of companies lack, or are unsure they have, the right data management practices for AI.
30%
of generative AI projects will be abandoned after proof of concept by the end of 2025.
88%
of companies use AI, yet only about one-third have begun to scale it.
Third-party research, quoted as published. Predictions are the source's forecasts, not measured results.
Responsible AI
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. Ask us how they apply to your project.
Before launch, every model is tested against metrics and a baseline agreed with you.
High-impact outputs are reviewed by a person. You decide where automation stops.
We keep PII to a minimum, and mask it or keep it out of prompts and training data where possible, under GDPR.
Where it matters, each score or prediction comes with reasons your team can check, for example with SHAP.
Once a model is live, we track drift, quality and cost, and plan when to retrain.
Built with the Act's risk classification, documentation and transparency duties in mind.
Our data stack
Stage 02 · Ingest
Azure Data Engineering
Pipelines, lakes and warehouses on Azure, secured and automated.
Explore Azure Data Engineering servicesWhat we deliver
Across every stage
All data engineering servicesWho we are
We are 50+ data engineers, data scientists, AI and product engineers, working from four offices in India, Germany, France and Bahrain. Since 2018 we have built the whole chain: pipelines and warehouses, dashboards and forecasting models, AI agents and assistants, and the web and mobile apps that put them in people's hands.
One team takes a project from the first workshop to launch and stays on to run it, so the people who scope the work are the people who build it. We work in short sprints you can follow, write down what we decide, and hand over code, data and IP that are yours, with no lock-in.



Offices
Proof
Official Snowflake, Databricks and Microsoft partners
Figures as of Oct 2026
Clients
Products we have designed, built and shipped for clients since 2018, our AI work first.
PetDX.aiAIPets & Animal CareWhy us
What you can hold us to on every engagement, from the first call to the handover.
Official Snowflake, Databricks and Microsoft partners.
From pipelines and models to the app your users open, built by one team.
Offices in Germany, France, Bahrain and India, across Europe, the Gulf and Asia.
ISO 27001 certified and GDPR-compliant, with an NDA signed on request.
Code, data and IP are yours, from the first commit to the final handover.
Every engagement is phased: stop after any phase, with everything handed over.
Industries
The sectors we build for most, and the data and AI work we do in each.
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
Transaction, customer and risk data engineered into governed pipelines that auditors and regulators can trace. Models for fraud, credit and reporting that explain every decision they make.
Fraud detection
Real-time scoring that flags unusual card, payment and account activity before transactions settle.
Credit risk scoring
Explainable models built on your own repayment and spending-pattern data, with the reasons behind each score.
Regulatory reporting
Governed pipelines that assemble regulatory and management reports from one tested source of truth.
Typical data and stack
Sales, inventory and customer data unified across stores, online and marketplaces. Forecasting, recommendations and pricing analytics that turn that data into better stock and margin decisions.
Demand forecasting
Forecasts by product, store and week that feed replenishment and cut both stockouts and overstock.
Recommendations
Tailored products and bundles on site, in app and in email, based on browsing and purchase history.
Pricing analytics
Price, promotion and markdown effects on volume and margin measured from your own sales data.
Typical data and stack
Tracking, order and warehouse data streamed into one operational picture of every shipment. Forecasting and document AI that cut manual checks and keep customers informed about arrival times.
Route and ETA prediction
Arrival times learned from traffic, delivery history and live tracking, updated as the day unfolds.
Inventory balancing
Stock levels balanced across warehouses against forecast demand, supplier lead times and service targets.
Shipment document automation
Bills of lading, invoices and customs forms read, checked and routed by LLMs, with human review.
Typical data and stack
Booking, guest and review data unified across properties and channels. Forecasting and tailored offers that help hotels and restaurants price smarter and give every guest a better stay.
Demand and pricing forecasts
Occupancy and rate forecasts by night, room type and channel, ready for revenue managers to act on.
Review sentiment
Guest reviews grouped by theme and property, so teams see what to fix first and what works.
Tailored guest offers
Offers, upgrades and messages tailored to each guest's stay history, preferences and booking channel.
Typical data and stack
Community and interest-based apps with feeds, chat, groups, events and video. Recommendations, moderation and engagement analytics that keep members active and the community safe.
Feed and match recommendations
Ranking models that put the right posts, people and groups in front of each member, tuned on real engagement.
Content moderation
Text and image classifiers that flag abuse, spam and unsafe media for review before it spreads.
Engagement analytics
Retention, cohort and funnel dashboards that show which features keep members coming back.
Typical data and stack
Learning, admissions and engagement data joined into one view of every student and course. Analytics and AI that help institutions support learners earlier and plan each intake with confidence.
Student-success prediction
Early signals of students who need support, surfaced while there is still time to help them.
Content recommendation
Next lessons, resources and practice matched to each learner's progress, pace and recent results.
Enrolment analytics
Applications, conversion and retention tracked from one data model, by course, campus and intake.
Typical data and stack
Listings, transactions and property data cleaned and combined so agencies and owners can price, sell and manage with evidence. Valuation, lead and portfolio models built on data you already hold.
Price estimation
Valuation models built on listings, past transactions and location data, giving a range instead of a guess.
Lead scoring
Enquiries ranked by how likely they are to view, offer or let, so agents follow up first.
Portfolio dashboards
Occupancy, yield, arrears and maintenance across every property in one view your team can trust.
Typical data and stack
Audio, stories and books produced with AI under editorial control. Pipelines that turn a prompt or an interview into on-air segments, narrated stories or printed books.
AI voice production
Scripts researched, written and voiced with text-to-speech, then scheduled to air with provider failover.
AI narration
Natural AI narrators, or a parent's own cloned voice, reading stories in an audio-first app.
Interview to book
An AI interviewer turns answers into narrative, then layout, checkout and print-on-demand.
Typical data and stack
Machine, quality and production data captured from the shop floor and joined with your ERP. Models that warn before failures, catch defects early and keep the production schedule realistic.
Predictive maintenance
Sensor and maintenance-log models that warn engineers days before a machine is likely to fail.
Visual quality inspection
Vision models that spot surface and assembly defects on the line as parts pass the camera.
Production planning
Demand and capacity forecasts that shape the schedule, material orders and shift plans each week.
Typical data and stack
Our work
Trending AI products, intelligent platforms and data-driven systems shipped for production.
AI Video AnalyticsAI Solutions: AI Video Analytics CCTV Intelligence Development
TraideFinderFinTech: TraideFinder – AI Stock and Crypto Market Scanner
Powerhouse CourierLogistics & Delivery: Powerhouse Courier – AI-Powered Dispatch & Delivery Management Platform
CallScoutCRM & Sales: CallScout – AI-Powered Outbound Calling Platform
AI Script-to-VoiceAI Solutions: AI Script-to-Voice – Automated Radio Broadcast Pipeline
PetDX.aiAI Solutions: PetDX.ai – AI Veterinary Diagnostics and Pet Care Platform
BullsAIAI Solutions: BullsAI – AI Market and Talent Intelligence PlatformTestimonials
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.
01 / 10
Readiness check
Five questions, two minutes. Get your level and the next three steps.
Pick the answer closest to where you are today.
Insights
AI DevelopmentThe demo went brilliantly. The AI assistant answered customer questions in seconds, leadership was impressed, and someone said, “Let’s roll this out everywhere.”
AI DevelopmentImagine spending thousands of dollars on AI tools, automating workflows, and introducing AI agents—only to discover six months later that your team is still doing most of the work manually. The tools are there.
AI DevelopmentIf you’ve spent any time researching how to make your business run more efficiently, you’ve almost certainly bumped into two terms that seem to get used interchangeably workflow automation and AI agents.
FAQ
Straight answers on scope, ownership, security and how we work. Can't find yours? Ask us directly.
business@equitysoft.inWith 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
Tell us about your data, AI or product challenge. We reply within one business day.
Tell us about your project
Free consultation · NDA on request