Sphere wins 2026 Global Recognition Award
Sphere Partners

The governed data layer under every AI answer

The SphereIQ Data Platform unifies structured and unstructured data, applies semantic context, and enforces policy-driven governance in one place — then serves it to Knowledge AI, Engram, Comply AI, and any application that needs it. One layer, one set of permissions, one audit trail.

Retrieval Engine — production throughput, low latency

Context Layer — semantic meaning, not keyword matching

Decision Rules — policy-driven, explainable, auditable

Universal Connectors — on-prem, multi-cloud, hybrid

Organizations around the world trust us

ideel
JFrog
Clearcover
91 Seconds
PHC
NextCapital
DigitalOcean
Enova
bp
Groupon
CreditNinja
Navy Pier
DoorDash
Gett
Experify
ideel
JFrog
Clearcover
91 Seconds
PHC
NextCapital
DigitalOcean
Enova
bp
Groupon
CreditNinja
Navy Pier
DoorDash
Gett
Experify

One platform. Four building blocks.

Most enterprises already have data, an LLM, and good intentions. What's missing is the layer that connects them without losing meaning, permissions, or an audit trail along the way.

SphereIQ Data Platform
1

Retrieval Engine

2

Context Layer

3

Decision Rules

4

Universal Connectors

Knowledge AIEngramComply AIYour Apps

Retrieval Engine

The production-grade core: fast retrieval, low latency, and reliable throughput under real concurrent load — not a demo-scale vector search that falls over at 50 users.

Context Layer

Semantic enrichment that adds meaning, relationships, and intent on top of raw text and records — so retrieval finds what a document means, not just what it says.

Decision Rules

Policy-driven, explainable outcomes. Business rules that produce deterministic, compliance-ready decisions with a full audit trail behind every one.

Universal Connectors

Secure integration across on-premises systems, multi-cloud, and hybrid environments — plus native MCP support for custom and proprietary sources.

How it works

From raw source to governed answer in four steps.

1

Connect

Structured and unstructured sources — databases, document repositories, SaaS systems — connect through native or MCP-based connectors. Access rules sync on connection, not at query time.

2

Enrich

Data is chunked, embedded, and tagged with semantic metadata: entities, relationships, provenance, and lineage. Structured and unstructured records share one context model.

3

Govern

Fine-grained permissions and business rules are enforced at the data layer itself, not bolted on downstream. Every access and every decision writes to an immutable audit log.

4

Serve

One governed layer feeds Knowledge AI, Engram, Comply AI, and any custom application over API or MCP — with the same permissions, the same lineage, every time.

One connection, one context model, one governance layer — read by every SphereIQ module and any application you build on top of it.

Capabilities

What the Data Platform does, specifically.

Structured + unstructured, unified

Databases, documents, and SaaS records live in one governed layer instead of a dozen disconnected silos each with their own access model.

Governance enforced at the data layer

Fine-grained permissions are checked where the data lives, not re-implemented in every application that queries it.

Semantic context & metadata

Entities, relationships, and intent are captured once and reused by every downstream module — Knowledge AI, Engram, and beyond.

RAG-ready vector store

A production pgvector-backed index built to reduce hallucinations, with retrieval quality tuned for enterprise document estates.

Business rules engine

Deterministic, explainable decisions for regulated workflows — the same rule produces the same outcome, every time, with a reason attached.

Lineage, provenance & audit trails

Every record traces back to its source system, every transformation is logged, every access is attributable to a user.

Multi-cloud & hybrid connectors

On-premises, AWS, Azure, GCP, or a mix — the platform meets data where it already lives instead of forcing a migration first.

MCP-native integration

Custom and proprietary systems connect through the Model Context Protocol, the same standard SphereIQ uses across its module suite.

Self-hosted deployment option

Docker Compose on your own infrastructure, with an air-gapped path available for federal, defence, and healthcare workloads.

Get the AI Buyer's Guide.

Discover the latest trends every organization should consider this year.

Built for regulated data estates

The same architecture underneath every SphereIQ module: self-hosted by default, permission-aware by design, and audit-ready without extra tooling.

Self-hosted by default

Runs inside your perimeter. Air-gapped deployment is available where regulation requires it.

Immutable audit log

Every query, every connector sync, every rule evaluation is written to an append-only log. Evidence export is one click.

PII detection at ingestion

Records containing personal data are flagged and access-restricted before they enter the index, not after.

Permission inheritance, not flattening

Every source system's access rules travel with the data. A public chatbot flattens entitlements; this platform never does.

Use Cases for a Governed Data Layer

How teams use the Data Platform once every module reads from the same governed source.

9 secto the right clause

Knowledge Discovery & Enterprise Search

A tier-1 asset manager searches 14 years of fund documentation through the same governed layer that feeds Knowledge AI — cutting disclosure-clause lookups from 40 minutes to 9 seconds, with every result permission-filtered.

90%faster research cycles

Deep Research & Due Diligence

A private equity research team runs cross-document diligence over data rooms, contracts, and financial models unified in one context layer — collapsing multi-day review cycles into hours.

100%decisions logged

Regulated Compliance Automation

An insurer runs underwriting exceptions through the Decision Rules engine — every approval, denial, and escalation is deterministic, explainable, and written to the same audit log Comply AI and Bulwark rely on.

1governed source of truth

Cross-Module Context Sharing

Knowledge AI, Engram, and Comply AI all read from the same Data Platform — so a permission change, a new connector, or a corrected record propagates everywhere at once instead of drifting across five separate pipelines.

Hear from

our clients
Lee Ebreo

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

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

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

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

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

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

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

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

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

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).

See the Data Platform on your own data.

A live 30-minute walkthrough on a sample of your actual sources. No slideware.

Sphere in Numbers

We understand that actions speak louder than words and numbers but here are some key facts about us.

Get the Right Talent now

0

Years of Excellence

0+

Projects Delivered

0

Countries

Globally diverse, community-focused

0+

Clients

top 20 average 8+ years

Frequently asked questions

It is the governed data layer beneath the SphereIQ suite: it unifies structured and unstructured data, adds semantic context, enforces policy-driven governance, and serves the result to Knowledge AI, Engram, Comply AI, and any custom application — through one permissions-aware, auditable layer.
Knowledge AI and Engram are applications built on top of this layer — RAG search and long-term memory, respectively. The Data Platform is the shared foundation: the connectors, semantic context, and governance rules that both modules (and others) read from, so permissions and lineage stay consistent across the whole suite.
Yes. The platform deploys via Docker Compose on your own infrastructure by default, with an air-gapped path available for federal, defence, and healthcare workloads.
Structured sources (databases, data warehouses, SaaS records) and unstructured sources (document repositories, SharePoint, Confluence, network drives) across on-premises, multi-cloud, and hybrid environments — plus custom and proprietary systems via MCP-based connectors.
Permissions and business rules are enforced at the data layer itself, not re-implemented per application. Every access, rule evaluation, and connector sync writes to an immutable audit log, with lineage traced back to the originating source system.
Typical rollout — connecting initial sources, configuring governance rules, and standing up the retrieval engine — runs three to six weeks depending on the number of source systems and the complexity of existing permission models.

Latest from Our Software & Product Blog