Solutions
Enterprise solutions that combine our practice areas into complete, production-grade outcomes. Each is delivered in your own cloud accounts, aligned to the frameworks you are assessed against, and transferred to your team.
Cloud Migration and Modernization
Move application portfolios from legacy and virtualized infrastructure to a governed AWS and Kubernetes platform, in controlled waves, without disrupting the business.
Business challenge
Enterprises carry portfolios of legacy applications on aging infrastructure, with rising operating cost, limited elasticity, and growing security exposure. Migration programs stall when the target platform, governance model, and cutover plan are not established before the first workload moves.
Our approach
We establish the target platform first: a multi-account AWS foundation and an Amazon EKS platform with identity, networking, guardrails, and delivery pipelines in place. Workloads are then assessed, grouped into waves, and migrated against defined cutover, validation, and rollback criteria.
Key capabilities
- Portfolio assessment and migration wave planning
- Multi-account, multi-region AWS landing zone delivered as code
- Re-platforming to containers and managed AWS services
- Data migration and cutover with validated rollback
- Operating model, runbooks, and knowledge transfer
- Decommissioning of legacy environments
Business outcomes
- Retirement of end-of-life infrastructure and its operating cost
- One standardized, auditable platform for every migrated workload
- Predictable cutovers with documented rollback
Aligned to
Technologies
RelatedCloud foundations and landing zonesKubernetes platform engineering
Enterprise Platform Engineering
A standardized internal developer platform that lets many teams ship securely on shared, governed infrastructure.
Business challenge
As engineering organizations grow, each team assembles its own pipelines, clusters, and security controls. The result is duplicated effort, an inconsistent security posture, and platform teams that cannot keep pace with demand.
Our approach
We build an internal developer platform on Amazon EKS and run it as a product: reproducible multi-cluster infrastructure, self-service golden paths, GitOps delivery with controlled promotion, a secured software supply chain, and tenant isolation enforced by policy.
Key capabilities
- Multi-cluster Amazon EKS reference architecture
- Self-service golden paths and tenant onboarding
- GitOps delivery with controlled environment promotion
- Signed artifacts, SBOMs, and admission policy
- Autoscaling and cost allocation by team
- Lifecycle management: scheduled upgrades and patching
Business outcomes
- A consistent security and compliance posture across teams
- Shorter lead time from commit to production
- Platform capacity that grows without proportional headcount
Aligned to
Technologies
RelatedKubernetes platform engineeringDevSecOps and software supply chain
Zero Trust Security Architecture
Replace implicit network trust with identity-based access, segmented workloads, and encrypted traffic from the edge to the data tier.
Business challenge
Perimeter security assumes that anything inside the network can be trusted. In multi-account and multi-cluster environments that assumption fails: one compromised workload or credential can move laterally. Regulators and California state cloud policy now expect zero trust architecture, and retired edge components such as Ingress NGINX add unpatched exposure.
Our approach
We implement zero trust across the identity, network, and workload layers: federated single sign-on with least-privilege roles, default-deny network policy with encrypted service-to-service traffic, a modern application edge on Gateway API and AWS WAF, and continuous verification through runtime detection.
Key capabilities
- Federated identity and least-privilege access model
- Microsegmentation with default-deny network policy
- Encrypted service-to-service traffic across clusters
- Application edge modernization on Gateway API with AWS WAF
- Secrets management and workload identity
- Runtime threat detection with alert routing
Business outcomes
- Reduced lateral movement and a smaller blast radius
- An internet-facing edge built on supported, patched components
- Access decisions that are logged and attributable
Aligned to
Technologies
RelatedKubernetes platform engineeringCloud security and continuous compliance
Regulatory Compliance Automation
Turn compliance from a periodic audit exercise into a continuous, evidenced property of the platform.
Business challenge
Compliance programs that rely on manual evidence collection are expensive, slow, and out of date the day after the audit. As frameworks move toward continuous assurance, organizations need controls that the platform enforces and evidence that is produced automatically.
Our approach
We map your control framework to technical controls, enforce them through policy as code, and build an evidence pipeline that continuously collects configuration state, access records, and change history into a tamper-evident store your auditors and security office can query.
Key capabilities
- Control matrix mapped to your regulatory framework
- Policy as code enforced at deployment and at runtime
- Centralized, tamper-evident audit logging
- Automated evidence collection and control reporting
- Vulnerability and patch management automation
- Audit preparation and assessor support
Business outcomes
- Audit evidence available on demand
- Control drift detected and corrected continuously
- Shorter audit preparation for engineering and security teams
Aligned to
Technologies
RelatedCloud security and continuous complianceDevSecOps and software supply chainInsight: Cal-Secure 2.0: what it means for agency platform teams
Enterprise Data Protection and Privacy
Protect regulated and personal data across production, analytics, and non-production environments.
Business challenge
Sensitive data rarely stays in one system. It is copied into test environments, analytics platforms, logs, and backups, each with weaker controls than production. Privacy regulation and breach liability follow the data wherever it goes.
Our approach
We classify sensitive data, encrypt it with customer-managed keys, restrict and record access, and remove it from places it does not need to be, using masking pipelines for non-production environments and redaction for logs and telemetry.
Key capabilities
- Sensitive data inventory and classification
- Encryption at rest and in transit with customer-managed keys
- Deterministic masking pipelines for non-production data
- Personal data redaction in logs and telemetry
- Fine-grained access control with complete access logging
- Backup protection and retention controls
Business outcomes
- Personal data confined to systems designed to protect it
- Realistic test data without privacy exposure
- A complete record of who accessed which records
Aligned to
Technologies
RelatedCloud security and continuous complianceData engineering and analytics platforms
Mission-Critical Resilience and Disaster Recovery
Engineer business-critical systems to meet defined availability and recovery objectives, and prove it through testing.
Business challenge
A recovery plan that has never been exercised is an assumption. For systems that process transactions, serve the public, or support clinical operations, the cost of an extended outage is measured in revenue, regulatory exposure, and public trust.
Our approach
We define recovery time and recovery point objectives with business owners, design multi-zone and multi-region architectures to meet them, instrument services end to end, and run scheduled failover and restoration exercises that produce documented results.
Key capabilities
- Recovery objectives agreed with business owners
- Multi-availability-zone and multi-region architecture
- Service-level objectives and error budgets
- End-to-end observability with OpenTelemetry
- Scheduled failover and restoration exercises
- Incident response process and post-incident review
Business outcomes
- Recovery capability demonstrated by test results
- Incidents detected by monitoring before customers report them
- Contingency evidence ready for auditors and regulators
Aligned to
Technologies
Enterprise Generative AI Platform
A governed foundation for generative AI in your own cloud, with the controls regulated organizations require.
Business challenge
Business units want generative AI now, while security, legal, and compliance teams need assurance about data handling, accuracy, and accountability. Unmanaged adoption produces shadow AI use and pilots that cannot pass a risk review.
Our approach
We build a central AI platform inside your AWS environment: a model gateway with access, usage, and cost controls; retrieval over approved data sources; an evaluation framework; guardrails and human review; and complete audit trails. Use cases are onboarded through a documented risk assessment.
Key capabilities
- Model gateway with access, usage, and cost controls
- Retrieval over approved data sources, with citations
- Evaluation framework and ongoing quality monitoring
- Guardrails, sensitive-data filtering, and human review
- Complete audit trail of prompts, sources, and outputs
- Use-case intake and risk assessment
Business outcomes
- A sanctioned AI capability that replaces unmanaged tools
- Answers traceable to approved sources
- Documented evidence for AI risk assessments
Aligned to
Technologies
RelatedApplied AI and LLM operationsAgentic AI development and operationsInsight: Buying generative AI in California government: what SAM 4986.9 requires
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