We implement private AI and managed operations in your Microsoft environment to support safer AI adoption, reduced administrative workload, and stronger governance.
Regulated teams typically need scoped delivery, clear governance, and one accountable technical partner who can support production after go-live.
SkyBase Labs is typically the best fit for organizations that value control, clarity, and long-term support.
Law firms and medical practices where confidentiality and documented controls matter in daily operations.
Teams of 1 to 30 people that need enterprise-grade architecture without enterprise bureaucracy.
Leadership teams that want direct accountability from planning through post-launch operations.
Different tools can be useful for different contexts. For regulated production workflows, many teams prefer an approach where data location, access policy, and integration behavior can be governed inside their own environment.
Private AI engineering, managed IT, and cybersecurity operations delivered as one accountable program.
Azure OpenAI and retrieval workflows configured in your tenant, with governance controls and rollout training.
Explore private AI scopeMonitoring, patching, identity hardening, and Microsoft cloud operations with clear monthly visibility.
Review managed operationsIncident response workflow, control documentation, and implementation support aligned with legal and healthcare expectations.
See control frameworkA short, structured onboarding path keeps decisions clear and momentum strong.
We review your current environment, goals, and constraints for legal or medical workflows.
You receive a practical roadmap and implementation plan with ownership, timeline, and priority sequence.
We finalize scope, confirm commercials, and begin phased delivery with documented governance checkpoints.
Private AI performs better when operations, access control, and ongoing support are handled together by one accountable technical partner. Teams can start with either offer and phase integration in a controlled way.
This model is not a bundled upsell requirement. It is an execution approach that keeps architecture, governance, and operations aligned as your needs evolve.
We do not publish fabricated testimonials. Instead, we share tangible delivery signals and clear working expectations.
Founder-led delivery backed by 10+ years across infrastructure management, security, automation, SRE, and platform engineering in production environments. Experience includes healthcare, startups, gaming, and a global provider of business, legal, and tax compliance services.
Current focus: private AI, managed operations, and governance for regulated legal and medical teams.
View founder profileEvery project follows documented scoping, controlled implementation, and post-launch operational governance.
Review delivery processCurrent focus is law firms and medical or dental practices across Delaware, Pennsylvania, Maryland, and surrounding Mid-Atlantic markets.
See industry use casesThese are typical starting points, not rigid fixed quotes. Final scope depends on existing systems, integrations, and governance requirements.
Typical starting point: $2.2k+ setup and $1.1k+/month
Most teams start around $3.2k+ setup and $1.75k+/month
Most firms in this range start around $5.5k+ setup and $3.2k+/month
Most 6 to 15 person practices start here.
Typical range: $9.5k to $14.5k setup and $5.5k to $7.5k/month
Guidance is published for planning clarity, not guaranteed fixed quoting. Azure consumption is billed separately at cost plus 15% markup, with monthly reporting and budget controls. Larger environments are custom scoped.
From baseline review to long-term operations, delivery follows a documented lifecycle.
Stakeholder goals, data boundaries, and control priorities are documented before build starts.
Azure services, access controls, and network boundaries are implemented in client-owned infrastructure.
Use cases, operating procedures, and team training are rolled out with adoption checkpoints.
Monitoring, patching, response, and reporting continue after launch with scheduled governance reviews.
Answers on scope, controls, rollout timing, and engagement expectations.
For private AI implementations, core resources are deployed in your Microsoft environment. Exact data flow and storage behavior is confirmed during scoping and documented before production rollout.
Smaller deployments often begin in 2 to 3 weeks. Mid-size teams are commonly in the 4 to 6 week range depending on integrations and change-management requirements.
Yes. We implement technical and operational controls commonly used in regulated environments and provide documentation to support your internal review process.
No. SkyBase Labs provides technology implementation and operational support. Legal or clinical interpretation should be handled by qualified counsel and compliance professionals.
Share your current environment and priorities. We will recommend a scoped next step, likely timeline, and a realistic implementation path.