ChatGPT-class experience
Clean, fast, familiar chat with folders, prompt library, edit-and-resend, stop generation, and dark or light themes. Adoption without a training program.
Products / Private AI Workspace
Your people already use AI. The question is whose servers it runs on.
A private enterprise AI platform — deployed on your infrastructure, speaking your languages, governed by your rules, audited to your regulator’s standard. Frontier AI, inside your perimeter.
21 years enterprise engineering300+ clients · 28 countriesNPS 75
Organizations around the world trust us
What it does
Banning AI does not stop AI. It only stops you seeing it.
Most institutions believe they have three options: ban it and push usage onto personal devices, allow a public tool and accept that prompts leave your jurisdiction, or spend eighteen months building it yourself. The Workspace is the third path — the platform your team would have built, delivered in weeks and owned by you.
Document intelligence
Upload and interrogate PDF, Office, CSV, JSON, logs, and images. Retrieval-augmented answers cited back to your own sources.
Arabic and English, natively
Full RTL interface, automatic language detection, and bilingual RAG across Arabic and English documents. Built for the Gulf, not translated for it.
Guardrails & moderation
Configurable input and output guardrails, prompt-injection detection, payment-card upload detection, and real-time admin alerts on policy breaches.
Audit everything
A centralized audit database records every login, prompt, response, upload, and admin change — exportable for compliance and retained to your policy.
Admin command center
Role-based access control with role-based feature visibility, per-user and per-group quotas, rate limits, usage analytics, and feedback metrics.
Model-agnostic core
Qwen, Llama, or frontier models via private endpoints — served on vLLM, switchable per use case, upgraded without downtime.
Deployed where your regulator lives
On-premise, in your private cloud, or in a named in-country sovereign cloud. Containerized on Docker and Kubernetes, air-gapped where required.
Real results
Proof, not projections
Every number comes from a named outcome, not a target or an estimate.
6h → sec
Cross-border tax research that took specialists six hours, answered in seconds by a private retrieval system.
60×
faster resolution across 35,000+ operational documents for a global air charter group — AI answers with citations, in production.
↳ Monarch Air Group — document intelligence
$1.2M
annual savings from AI-driven back-office automation for an oil & gas accounting provider.
Who it's built for
Built for institutions that answer to a regulator
The Workspace is designed for organizations where data residency, auditability, and access control decide whether an AI project is allowed to exist at all.
Banking & Financial Services
Credit, risk, and compliance teams working on customer data that cannot leave the jurisdiction.
Insurance
Claims, underwriting, and policy workflows grounded in your own documents with a full audit trail.
Government & Public Sector
In-country sovereign deployment with source-code ownership and escrow where procurement requires it.
Healthcare
Clinical and administrative knowledge retrieval inside the perimeter, with role-based access enforced per query.
Energy & Utilities
Operational documents, standards, and field procedures made answerable without exposing them to a public model.
Telecom & Regulated Enterprise
Large internal knowledge estates and strict data-handling mandates across multiple regions.
In their own words
Verified by the people who signed off on it
“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
The analyst on your credit desk still has a deadline.
The only question is whether the AI she uses tomorrow is the one that leaks, or the one you gave her. A 30-minute working session on your environment, your regulator, and your fastest safe path to production.
Book a DemoFAQ
Straight answers
A private AI workspace is a private AI platform with a ChatGPT-class chat experience, deployed entirely on your own infrastructure — on-premise, in a private cloud, or in an in-country sovereign cloud — so prompts, documents, and model outputs never leave your jurisdiction or control. Sphere Private AI Workspace adds the enterprise layer: SSO, role-based access control, configurable guardrails, prompt-injection detection, and a complete audit trail of every interaction.
Yes. The Workspace runs containerized on Docker and Kubernetes in your data center or approved sovereign cloud, serves open models such as Qwen and Llama on vLLM (or frontier models via private endpoints), and meets banking requirements: TLS 1.3 in transit, AES-256 at rest, Entra ID SSO over SAML 2.0/OIDC, maker-checker patterns, exportable audit logs, penetration-test reports, and source-code escrow.
Yes — natively, not as an afterthought. Full Arabic and English interface with right-to-left (RTL) layout, automatic language detection, bilingual retrieval-augmented generation over Arabic and English documents, and Arabic/English speech-to-text voice input.
A typical deployment reaches production in 8–12 weeks: weeks 1–2 for diagnostic and architecture, weeks 3–8 for deployment and hardening including penetration testing, and weeks 9–12 for pilot launch, hands-on admin training, and full documentation and source-code handover.
You do. Sphere delivers full source code, deployment scripts, architecture and operations documentation, and hands-on knowledge transfer at project completion — with escrow arrangements available where procurement requires them.
The model layer is agnostic by design: open-weight models such as Qwen and Llama served on vLLM inside your environment, or frontier models accessed through private cloud endpoints. Administrators switch between model versions and sizes per use case, and upgrades deploy without downtime.
Governance is enforced at three layers: configurable guardrails on inputs and outputs, domain restriction of responses, detection of sensitive-data uploads such as payment-card information, and real-time admin notifications when policy boundaries or injection attempts are detected. Every event lands in the central audit database — exportable for your compliance team.
Yes — native federation with Microsoft Entra ID, Okta, Ping, or any SAML 2.0 / OAuth 2.0 / OIDC identity provider. For regulated buyers this is typically the first gate a vendor has to clear: no shadow identity system, no separate login to manage.
Every authentication event, prompt, AI-generated response, file upload and download, session detail, and admin change — timestamped, attributable to a specific user, and exportable for your compliance and regulatory reporting. This is the single most-cited requirement across regulated-industry AI RFPs, and it is asked twice in most of them: once functionally, once at the infrastructure level.
Yes, and we will name the specific facility. Data residency is usually the requirement that determines whether a vendor is even eligible to bid — a vague answer like "we support cloud deployment" does not clear that bar. The Workspace deploys on-premise, in your private cloud, or in a named in-country or in-region sovereign cloud, aligned to your jurisdiction’s specific data protection law.
Yes — regulated buyers weight peer references (same industry, same region, comparable data-residency constraints) far more heavily than a general enterprise client list, and we answer accordingly with implementation case studies from comparable institutions rather than logo-count.