Data Science and
Analytics Services 

Turn Data
into Actionable Intelligence

Many companies are good at collecting data. Others excel at analyzing it. Sphere is expert in both — and in every critical step needed to turn raw data into trusted, actionable intelligence.

Our services span data aggregation, architecture modernization, governance, and advanced analytics, all built to help you operate at production scale. Whether you need real-time insights, AI model deployment, or a single source of truth, we make sure your data is clean, compliant, connected, and ready to drive results.

With Sphere, you can paint a complete picture of your business’ collected data and have the expert knowledge to act upon it.

Talk to us about your data challenges

Our Services

Data Aggregation & Integration

Data today flows from SaaS apps, IoT devices, ERP systems, and public sources — often in incompatible formats. Sphere designs and implements scalable, compliant data pipelines (ETL/ELT) and modern data warehouses or lakehouses, optimized for multi-cloud and hybrid environments. The result: a unified, governed dataset that’s ready for analytics and

Business Intelligence & Real-Time Reporting

We go beyond static dashboards. Sphere implements Tableau, Power BI, Qlik, and open-source BI tools with streaming data support and AI-driven alerts, so decision-makers act on events as they happen. Internal KPI measurement, external partner reporting, and embedded analytics are tailored to your workflows.

AI/ML-Driven Data Science

We build and scale ML systems that don’t stop at proof-of-concept. Sphere handles full-lifecycle AI — from data preparation and model training to deployment, monitoring, and retraining pipelines. Our solutions predict demand, detect anomalies, personalize experiences, and automate actions — always with explainability, bias testing, and regulatory alignment built in.

Data Engineering for Modern Enterprises

Data engineering is no longer about pipelines alone. It’s about reliability, latency, and governance. Sphere’s engineers design for scale, speed, and compliance, enabling your Data Scientists to generate statistically sound results without bias. We support real-time ingestion, event streaming, and API-driven architectures for faster, better decisions.

Data Strategy

Your data strategy should align with both today’s needs and tomorrow’s regulations. Sphere helps you build a governed, AI-ready roadmap, coordinating people, process, and technology to adopt a data-driven culture, meet compliance requirements (AI Act, HIPAA, CCPA), and increase analytical maturity.

Data Architecture Assessment

We start with where you are. Together, we design a future-state architecture — modular, secure, and interoperable across cloud and on-prem — and create a plan to get there without disrupting your business operations.

Should You Implement a Single Source of Truth? 

An SSOT ensures your entire organization makes decisions from the same trusted dataset. Without it, you risk low trust, inconsistent usage, conflicting metrics, and ultimately lost ROI.

As companies progress in their data maturity, the focus shifts from simply maintaining data integrity to leveraging trusted data for competitive advantage. Achieving this is complex — governance, integration, and adoption hurdles can stall progress. Sphere has helped organizations overcome these barriers, delivering SSOT architectures that scale, remain compliant, and drive measurable business outcomes.

Why It Matters

FROM

Conflicting numbers from multiple reports

TO

Single source of truth everyone agrees on

FROM

Hesitant decision-making

TO

Confident, data-driven leadership

FROM

Ad hoc, manual reporting

TO

Governed, reusable insights

FROM

Low AI/ML effectiveness

TO

Trusted, clean training data powering real results

Sphere’s ML Checkup & Acceleration Services

We perform a comprehensive health assessment of your current data and ML environment, covering data quality, governance readiness, architecture scalability, and compliance alignment. The checkup identifies technical gaps, operational risks, and opportunities for improvement — from missing training data to insufficient monitoring pipelines. You’ll receive a detailed recommendations report with prioritized actions to move toward a fully production-ready ML capability.

Our 1-on-1 strategic consulting sessions are designed to accelerate your ML adoption without wasted investment. Together, we define high-impact use cases, map dependencies, and evaluate data readiness. The output is a clear, step-by-step ML roadmap that aligns business objectives, compliance requirements, and technical feasibility. We also provide resource planning guidance — including skillset needs, cloud/compute budgets, and integration timelines — so you know exactly how to execute.

For organizations with existing ML systems, we run deep-dive performance audits across multiple dimensions:

  • Model performance – accuracy, recall, precision, and drift detection

  • Architecture efficiency – scalability, redundancy, and cost efficiency

  • Data integrity – quality, bias detection, and lineage verification

  • Operational readiness – latency, fault tolerance, and retraining pipelines

The result is a set of actionable optimization plans to improve speed, reduce costs, and maintain accuracy while meeting 2025 AI governance and ethical standards.

We take your ML vision from proof-of-concept to enterprise-wide adoption. This includes:

  1. Build – Data preparation, model design, and infrastructure setup (cloud, on-prem, or hybrid).

  2. Operate – Model deployment, production monitoring, retraining cycles, and MLOps automation.

  3. Transfer – Full operational hand-off to your team with documentation, code repositories, and hands-on training.

Sphere ensures your ML systems are battle-tested, compliant, and easy to maintain, so your team can run them independently long after deployment.

Data Infrastructure That Works Now — and in 5 Years

We combine AI-driven forecasting with governed data pipelines to help you act before the market moves.

Finance
Healthcare
Retail
Banking

AI-Powered Onboarding Platform Helps PetroLedger Save $1.2M Annually

Sphere built a generative AI onboarding platform
that cut ramp-up time by 120% and saved $1.2M annually.
AI-Powered Onboarding Platform Helps PetroLedger Save $1.2M Annually

AI-Powered Automation Boosts Order Accuracy and Reduces Costs by 50%

Sphere deployed an intelligent order entry system for a leading medtech company, cutting manual work in half and slashing order processing errors.
AI-Powered Automation Boosts Order Accuracy and Reduces Costs by 50%

Generative AI Helps Retailer Save $7.5M in Working Capital

Sphere developed an AI-driven inventory planning engine that increased accuracy by 83%, reduced overstocking, and unlocked millions in capital.
Generative AI Helps Retailer Save $7.5M in Working Capital

AI Summarization Platform Cuts Research Time by 70% for Financial Teams

Sphere built a GenAI tool that analyzes documents, extracts key insights, and generates executive-ready summaries, turning hours of reading into minutes.
AI Summarization Platform Cuts Research Time by 70% for Financial Teams

Hear From Our Clients

Sphere Partners
Selah Ben-Haim VP of Engineering at Prominence Advisors

Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).

Sphere Partners
Ben Crawford Senior Product Manager at Enova Financial

I would expect to be delighted. It’s been a really positive experience, working with Sphere, and I would expect you to have the same.

Sphere Partners
Mark Friedgan CEO at CreditNinja

Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. They bring innovative and well-considered solutions, consistently surpassing my expectations.

Sphere Partners
René Pfitzner Co-Founder at Experify

Sphere provided excellent full-stack development manpower to augment our team and work with us.

Sphere Partners
Bruce Burdick Chief Information Officer at Integra Credit

We've been working with Sphere and its excellent consultants since our founding. Their combination of offshore talent, pricing, and shift offsetting is hard to beat. They provide crucial augmentation to our in-house team. We simply couldn't achieve our production ambitions without their service.

Sphere Partners
Jemal Swoboda CEO at Dabble

The resources and developers that Sphere Software provides are skilled and have the required technical expertise to complete their tasks successfully, with the team easily scaled in either direction. The deliverables are always high-quality.

Sphere Partners
Arthur Tretyak Founder and CEO at IntegraCredit

With Sphere, we were able to migrate in half the time it would take to train an additional FTE…

Sphere Partners
Lee Ebreo VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system. We augmented our development team capabilities using Sphere’s developer, who works very well with our Dev Lead in Chicago. Sphere’s developer was an expert in the new system, and continues to be an expert as we evolve it.

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Contact our Data Experts

Flexible, fast, and focused — Sphere solves your tech and staffing challenges as you scale.

Luke Suneja

Client Partner

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20

Years of Experience

4.9*

Clutch.co Review Score

97%

Client retention rate

1600+

Completed Projects

Join 350+ Satisfied Clients

Latest from Our Data Trust Blog

Frequently asked question

Data analytics services involve collecting, processing, and analyzing data to uncover patterns, trends, and insights that help businesses make informed decisions. These services can include data engineering, business intelligence (BI), predictive analytics, and machine learning implementation.

Data analytics helps businesses identify opportunities, optimize operations, reduce costs, and improve customer experiences. By using advanced tools and AI-driven models, companies can predict trends, detect anomalies, and act on real-time insights to gain a competitive edge.

Data science focuses on building models and algorithms to make predictions or automate decisions, often using machine learning and AI techniques. Data analytics typically refers to the process of examining datasets to extract meaningful insights, often using BI tools, dashboards, and reporting systems.

A single source of truth is a centralized, trusted data repository that ensures everyone in an organization uses the same accurate and up-to-date information for decision-making. SSOT eliminates discrepancies, reduces errors, and improves collaboration across teams.

Machine learning and AI enhance data analytics by automating data processing, identifying hidden patterns, and generating predictive insights. These technologies allow businesses to act proactively rather than reactively, improving decision-making speed and accuracy.

The timeline depends on project complexity. A basic BI dashboard might take a few weeks, while enterprise-scale data platforms with AI integration can take several months. Agile delivery approaches often provide early value within the first 6–8 weeks.

Key trends include real-time analytics, AI governance and compliance, data mesh architecture, multi-cloud data strategies, and the integration of generative AI into BI platforms. Businesses are focusing on trustworthy, explainable insights rather than just big data volume.

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