Get Started

Data Science with Python - from notebooks to production.

Your data, your industry, your growth. From forecasting demand to detecting fraud, Python transforms scattered data into production-ready pipelines, models, and dashboards.

Retail & E-commerce Finance & Insurance Healthcare & Pharma Logistics & Manufacturing SaaS & B2B Real Estate
Contact Us Choose Your Industry
TRUSTED BY
JPMorgan
Roche
Credit Suisse
Orange
UPS
Sovo
Whisby

Real-World Python Applications

See how data science and MLOps translate into everyday business impact across industries.

Retail & E-commerce: sell smarter

  • Forecast demand by product & location
  • Dynamic pricing and promotion engines
  • Recommendation systems that boost basket size
  • Catch anomalies in margins and stock early
Impact: +2–6% sales, −10–20% overstock

Finance & Insurance: reduce risk

  • Credit scoring with explainability for regulators
  • Fraud detection running in real time
  • AML monitoring that scales with transactions
  • Stress tests and portfolio simulations
Impact: 30–60% fewer fraud losses without hurting UX

Telco & Media: keep subscribers longer

  • Churn prediction + proactive retention offers
  • Real-time service quality monitoring
  • Behavior-based customer segmentation
  • Content recommendations powered by NLP
Impact: −3–7 pp churn, +10–20% ARPU uplift

Healthcare & Pharma: safer decisions

  • Clean and validate clinical data automatically
  • De-identify documents (PII redaction)
  • Forecast demand for meds, labs, and staff
  • Compliance dashboards with full audit trail
Impact: fewer errors, faster turnaround, audit-ready

Logistics & Manufacturing: move faster

  • Optimize routes and loading with ML heuristics
  • Predictive maintenance on machines & fleets
  • Computer vision QA on production lines
  • Smarter supply & production planning
Impact: −8–15% transport cost, −20–40% downtime

SaaS & B2B: grow accounts faster

  • Lead scoring & pipeline prioritization
  • Usage analytics for value-based pricing
  • Early warning on product adoption drop
  • AI support assistants trained on your docs
Impact: +10–25% conversion, faster time-to-value
Contact Us Explore Services

Hitting limits with your Python data stack?

We turn fragmented notebooks into reliable, production-grade pipelines and models.

Tired of pipelines breaking or running too slow?
Get stable, automated workflows with Airflow/Prefect and dbt.
Frustrated that models perform well in notebooks but fail in production?
Validate properly and monitor drift with feature stores.
Struggling to prove compliance or track experiments?
Gain full visibility with MLflow/W&B and clear lineage.

What You Gain with Python Specialists

From data ingestion to model serving and lifecycle management.

Data Engineering (Python)

  • ETL/ELT with Airflow/Prefect, dbt
  • Batch & streaming (Spark/Dask/Kafka)
  • Data quality: Pandera/Great Expectations
  • Warehouses: BigQuery/Snowflake/Redshift

ML & Predictive Modeling

  • scikit-learn · XGBoost/LightGBM/CatBoost
  • PyTorch/TensorFlow training & tuning
  • Feature stores · robust validation
  • Explainability & bias checks

MLOps & Model Serving

  • MLflow/W&B · experiment tracking
  • APIs with FastAPI, gRPC, Triton
  • Docker/K8s, autoscaling, GPU
  • Monitoring, drift & retraining loops

NLP & Document AI

  • Classification, NER, topic modeling
  • RAG pipelines (vector stores, embeddings)
  • Summarization, QA, evaluation harness
  • PII handling & redaction

Time Series & Forecasting

  • Classical (ARIMA/Prophet)
  • Gradient boosting & deep TS
  • Feature pipelines & holiday effects
  • Backtesting & scenario stress

Analytics & Experimentation

  • Exploratory analysis (pandas/Polars)
  • AB testing & causal inference
  • Dashboards: Streamlit/Plotly
  • Data governance & documentation
Contact Us

Python Tech Stack

Your project runs on the same Python stack used by top data teams worldwide - future-proof and trusted at scale.

NumPy
NumPy
scikit-learn
scikit-learn
PyTorch
PyTorch
TensorFlow
TensorFlow
Apache Spark
Apache Spark
dbt
dbt
Kafka
Kafka
BigQuery
BigQuery
Snowflake
Snowflake
AWS
AWS
GCP
GCP
Azure
Azure
Weights & Biases
Weights & Biases

Our Python Delivery Process

Every step gives you a tangible result: from quick prototypes that prove value, to pipelines and APIs you can run in production.

1) Discovery & Data Audit

Source mapping, data contracts, risks, KPIs, baseline.

2) Prototyping & EDA

Notebooks (pandas/Polars), features, candidate models.

3) Engineering & MLOps

Pipelines (Airflow/Prefect/dbt), MLflow/W&B, CI/CD, tests.

4) Serving & Monitoring

FastAPI services, autoscaling, drift/quality dashboards.

What Lands in Your Hands

Concrete artifacts and operational capabilities.

1) Production Pipelines

Airflow/Prefect DAGs, dbt models, data tests.

2) Models & Experiment Logs

MLflow/W&B, lineage, versioned datasets.

3) APIs & Dashboards

FastAPI services, Streamlit/Plotly monitoring.

4) Docs & Handover

Runbooks, IaC manifests, training sessions.

Google Cloud Partner badge

We’re an official Google Cloud Partner

Verified expertise in AI, data, and scalable infrastructure — delivered with best practices and governance.

Generative AI
Data & ML
MLOps
Security
Integrations
Cloud
See Our Partner Profile Contact Us

We also deliver on other major platforms — we’ll recommend what fits your product best.

Turn your Python stack into a growth engine.

Share your goals - and get a clear plan to move from idea to measurable business impact.

Contact Us
Contact us

Have data, models, or just an idea? Let’s architect it in Python.

Our Location

Poznan, Poland

Call 🇬🇧 🇵🇱

+48 509-992-212

E-mail

info@inigra.eu

Let’s talk Python & Data

Share your goals — we’ll outline the fastest path to value.






    This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

    Inigra Sp. z o.o.

    Office: Piekary 7, Poznań, Poland

    VAT-ID: 6492316515

    +48 509-992-212

    info@inigra.eu

    About Us

    google cloud

    Services

    © 2025 Inigra

    English