Sphere AI Foundry™ embeds elite AI engineering pods and human-in-the-loop enablement into your organization to build, train, and deploy AI systems that are accurate, secure, governed, and production-ready.
A New Model for
Enterprise AI
Cross-functional delivery teams that integrate directly into your environment to accelerate AI initiatives. Each Pod can include:
AI Enablement & Model Shaping
Human expertise where AI needs it most. We work alongside you throughout your AI journey, from prototype to scale and governance.
RLHF & evaluation
RLHF improves a model using human preference feedback – people judge outputs, and the model is adjusted toward what “good” looks like in your operations. Evaluation is the test harness that proves quality before release and catches regressions and drift after deployment.
Human-in-the-loop workflows
Human-in-the-loop means AI can draft or recommend, but humans approve or override at defined steps based on risk and uncertainty. The workflow also logs decisions and handoffs so it stays controllable and auditable.
Domain-specific shaping
Domain shaping makes the system behave like your business by teaching terminology, policies, decision criteria, and edge cases. It’s typically a mix of curated examples, targeted tuning, and domain-specific evaluation.
Bias, trust & security review
This is the gatekeeping layer: bias checks, privacy/data leakage controls, access boundaries, and adversarial testing (including prompt injection). It’s where governance is validated – what the system can do, who can use it, and how it’s inspected later.
RAG + knowledge grounding
RAG connects the model to approved internal sources so responses come from retrieved evidence, not guesswork. Done right, it improves accuracy, keeps answers current, and makes outputs traceable.
Agentic workflows & orchestration
Agentic workflows handle multi-step tasks by planning actions, calling tools/APIs, and verifying results along the way. Orchestration is the control layer that enforces rules, approvals, and safe execution across systems.
RLHF & evaluation
RLHF improves a model using human preference feedback – people judge outputs, and the model is adjusted toward what “good” looks like in your operations. Evaluation is the test harness that proves quality before release and catches regressions and drift after deployment.
Human-in-the-loop workflows
Human-in-the-loop means AI can draft or recommend, but humans approve or override at defined steps based on risk and uncertainty. The workflow also logs decisions and handoffs so it stays controllable and auditable.
Domain-specific shaping
Domain shaping makes the system behave like your business by teaching terminology, policies, decision criteria, and edge cases. It’s typically a mix of curated examples, targeted tuning, and domain-specific evaluation.
Bias, trust & security review
This is the gatekeeping layer: bias checks, privacy/data leakage controls, access boundaries, and adversarial testing (including prompt injection). It’s where governance is validated – what the system can do, who can use it, and how it’s inspected later.
RAG + knowledge grounding
RAG connects the model to approved internal sources so responses come from retrieved evidence, not guesswork. Done right, it improves accuracy, keeps answers current, and makes outputs traceable.
Agentic workflows & orchestration
Agentic workflows handle multi-step tasks by planning actions, calling tools/APIs, and verifying results along the way. Orchestration is the control layer that enforces rules, approvals, and safe execution across systems.
Who We Serve
We enable AI that meets the standards of:
Enterprises
Scaling AI beyond PoCs into production
AI-native companies
Accelerating product delivery & reliability
Regulated industries
Where privacy & security matter
Build AI You Can Defend in an Audit
Governance-first delivery with evaluation, human-in-the-loop controls, and secure MLOps — so models stay accurate, traceable, and compliant.
Start nowWhy Sphere AI Foundry™
When AI has to work in production – under security, compliance, and real user pressure – you need more than extra hands.
Sphere AI Foundry™ builds and delivers operational AI systems end-to-end, focused on measurable business outcomes: faster decision cycles, lower operational risk, and AI that performs reliably inside real workflows. Teams ship to production faster and retain full control over governance, cost, and system behavior.
- Production-grade engineering
- Secure enterprise deployments
- Governed human-in-the-loop
- RLHF & domain-driven shaping
- RAG-powered accuracy & grounding
- Agentic orchestration for workflow automation
Use Case for
Your AI Foundry
Logistics
from passive dashboards to autonomous decisions
Challenge
A global logistics provider faced fragmented data, manual route planning, and unreliable ETAs. Existing analytics showed problems but didn’t act on them.
Solution
Sphere AI Foundry embedded an AI engineering pod to build a production routing system:
- RAG pipelines grounding decisions in delivery history, traffic, weather, and ERP data
- Agentic AI for dynamic route optimization
- RLHF to improve dispatcher-level decision accuracy
- Human-in-the-loop controls for exceptions and overrides
Outcomes
- 19% improvement in ETA accuracy
- 27% reduction in manual planning time
- Agent-managed routing for 60%+ of deliveries
- Full auditability and explainability for operations teams
Financial Services
scaling AI decisions without breaking compliance
Challenge
A financial services firm wanted to automate underwriting and risk assessment, but AI outputs lacked consistency, explainability, and regulatory confidence.
Solution
Sphere AI Foundry delivered a governed decisioning system:
- RAG grounding models in policy documents, historical claims, and regulatory rules
- Human-in-the-loop review for edge cases and high-risk decisions
- RLHF to align outputs with underwriter judgment
- Secure MLOps with full decision traceability
Outcomes
- 35% faster decision turnaround
- Reduced manual review workload by 40%
- Consistent, explainable decisions aligned with policy
- Audit-ready AI workflows approved by compliance teams
Enterprise Operations
turning institutional knowledge into an operational asset
Challenge
A large enterprise struggled with siloed documentation, tribal knowledge loss, and slow decision-making across engineering and operations teams.
Solution
Sphere AI Foundry built an internal knowledge intelligence layer:
- RAG systems unifying documents, tickets, SOPs, and historical decisions
- Agentic assistants embedded in daily workflows
- Human validation loops to prevent hallucinations
- Continuous evaluation to keep knowledge current and trusted
Outcomes
- 50% reduction in time spent searching for information
- Faster onboarding of new employees
- Fewer operational errors caused by outdated knowledge
- A trusted, explainable AI layer across teams
Engagement Models
Flexible. Scalable. Enterprise-ready.
Monthly AI Engineering Pods
Embedded AI delivery teams that ship production features every month inside your environment.
Project-Based AI Enablement
A focused engagement to take one AI use case from requirements to production.
Subscription HITL & RLHF Programs
Ongoing human feedback + evaluation that continuously improves accuracy, safety, and reliability in live AI systems.
Hear From
Our ClientsHear From Our Clients
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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Sphere in Numbers
We understand that actions speak louder than words and numbers but here are some key facts about us.
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Years of Excellence
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Projects Delivered
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Countries
Globally diverse, community-focused
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Clients
top 20 average 8+ years
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