Different systems tell different stories
Customer, product, financial, and operational records drift across tools, creating manual reconciliation work.
Sphere helps teams connect, govern, and modernize the data behind reporting, automation, RAG systems, agents, and operational decisions without forcing a full replatform.




Most teams have plenty of data. The harder issue is that the data is duplicated, stale, siloed, or difficult to trust when it matters.
Customer, product, financial, and operational records drift across tools, creating manual reconciliation work.
Business users wait on data teams for standard answers instead of using trusted self-service reporting.
Teams need to know who owns each source, who can access it, and how changes are tracked.
RAG systems, agents, and dashboards are only as reliable as the source layer beneath them.
The goal is not to replace every system. The goal is to make the data behind those systems reliable, traceable, and usable for the teams and tools that depend on it.
This is the foundation that makes reporting, RAG, agents, and workflow automation safer to deploy. When the data layer is governed, the systems above it become easier to trust.
A strong Data Intelligence page needs to show what changes operationally, not just list capabilities.
Sphere built a self-service reporting system with dynamic dashboards so business users could answer common questions without waiting on a manual reporting queue.
Standard questions required a new ticket and depended on an already stretched data team.
Common reports became accessible through a centralized platform with reusable dashboards and cleaner data access.
Each layer supports a clearer operating model: cleaner pipelines, stronger governance, better reporting, and a safer path to enterprise AI.
Ingestion, pipelines, warehousing, real-time processing, and integrations that connect the systems your teams already use.
Start hereOwnership, access rules, source tracking, and auditability so teams understand where data came from and who should use it.
QuestionsLegacy migration, cloud platforms, data lakes, and architecture improvements when the current environment cannot support scale.
See the storyPrepare trusted data for dashboards, RAG systems, agents, and decision-support tools that need reliable source material.
Talk to SphereNot every organization needs a rebuild. Some need clarity first. Others need a focused team to build the governed layer and put it into production.
Map your data landscape, identify the highest-risk gaps, and create a practical remediation plan before a larger build begins.
A Sphere team builds the governed pipeline, integrations, dashboards, and monitoring inside your environment.
Prepare approved sources, access rules, indexing, and lineage before enterprise AI is connected to critical business knowledge.
Sphere starts with the business use cases, then maps the data, systems, owners, and controls required to support them.
Review your data sources, reporting pain points, system dependencies, and priority use cases.
Rank the highest-impact gaps in freshness, fragmentation, access, lineage, and ownership.
Implement the pipelines, integrations, dashboards, controls, and monitoring needed for production use.
Extend the governed layer to additional teams, data sources, dashboards, and AI-enabled workflows.

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 and if we did not partner with Sphere to help us achieve our goals.

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).

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.

Mark Friedgan
CEO at CreditNinja
Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. As an offshore team, they have been an integral part of our organization and we plan to continue growing with them.

René Pfitzner
Co-Founder at Experify
Sphere provided excellent full-stack development manpower to augment our team and help push our product forward. They are easy to work with, tech-savvy and proactive.

Bruce Burdick
Chief Information Officer at Integra Credit
We've been working with Sphere and its excellent consultants since our founding. I've found that they are true partners in the success of our business.

Jemal Swoboda
CEO at Dabble
The resources and developers that Sphere Software provides are skilled and have the required technical expertise, but more importantly, they have helped us build a culture of excellence within our team.

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… and for a fraction of the cost. Our experience with Sphere has been exceptional.

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 and if we did not partner with Sphere to help us achieve our goals.

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).

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Usually, no. Sphere typically works with the systems already in place and adds the missing governance, pipeline, access-control, and reporting layers. Full replatforming is only recommended when the current environment cannot support the business goal.
RAG systems and agents depend on trusted source material. Data Intelligence work helps prepare approved sources, permissions, freshness rules, lineage, and retrieval-ready structure before AI is connected to critical business information.
The assessment maps source systems, data owners, access requirements, reporting gaps, freshness risks, and priority use cases. The output is a practical roadmap ranked by impact and implementation effort.
A readiness assessment is typically 2-3 weeks. A first production pipeline often falls in the 6-12 week range, depending on the number of systems, integrations, and governance requirements involved.
Start with a readiness review, a focused engineering pod, or an AI-readiness plan for RAG, agents, and operational reporting.
Please provide your contact details, and our team will get back to you promptly.