Products / Sphere Data Platform
Ingestion, pipelines, data quality, and governance-ready storage — the unglamorous layer that decides whether every AI initiative above it succeeds or stalls.
21 years enterprise engineering300+ clients · 28 countriesNPS 75
What it does
Most AI initiatives do not fail on the model. They fail on the data underneath it — untracked, unvalidated, and ungoverned.
Batch and streaming ingestion from ERP, CRM, ticketing, warehouses, and file stores — orchestrated, versioned, and resumable.
Proven across 6+ source-system types in a single deployment — two ERPs, two CRMs, and two estimating systems — without a rip-and-replace of the underlying stack.
Validation rules, anomaly detection, and lineage tracking so a questionable number can be traced to its source.
One deployment reconciled 14,000+ estimates across incompatible legacy cost models and surfaced a $680K/year discrepancy hiding in the data itself.
Role-based access, encryption, and immutable audit trails from day one.
Access boundaries are inherited from source systems, not flattened — a unified layer never grants visibility a user didn't already have.
Company Brain, Support Intelligence, AI Factory, and Governance query the same governed data.
Runs in production with hourly sync and zero access-control exceptions across 90 days of governed live queries.
Real results
Every number comes from a named outcome, not a target or an estimate.
$1.2M
annual savings from an institutional-knowledge platform built on Sphere Data Platform
250
daily active users on a self-service reporting platform
$680K/yr
recovered from a markup-formula discrepancy hiding across two merged estimating systems — surfaced by unifying 612 duplicate records into 187 governed golden records at 94% match confidence.
Who it's built for
Sphere works with organizations that need modern software, trusted AI, and data systems that can support regulated, high-stakes operations.
AI onboarding, compliance workflows, analytics, automation, and secure modernization.
Secure internal tools, data workflows, patient-facing systems, and regulated AI use cases.
Operational intelligence, modernization, process automation, and AI-assisted validation.
Claims workflows, customer operations, knowledge retrieval, and governed AI systems.
Complex data environments, field operations, asset-heavy workflows, and platform modernization.
Technical due diligence, carve-outs, operational foundations, and delivery support.
In their own words
“Sphere consistently demonstrated a high level of accountability, technical expertise, and executive partnership.”Abhishek Karan — BP
“Their combination of product thinking, engineering expertise, and execution discipline enabled impactful solutions.”Matt Norman — DigitalOcean
“Sphere approached AI transformation the right way — starting with workflows and data governance.”Ilya Kaminsky — Summit Financial Management
Where to start
A 30-minute walkthrough of how Sphere Data Platform grounds the rest of the stack — tailored to your systems, not a generic script.
Book a Demo