Our Expertise
Engineered disciplines.
Composable by design.
Five senior engineering practices, staffed by architects and engineers who run these disciplines in production every week. They compose into a single accountable pod for your engagement, not a relay race of vendors.
Secure AI & Agentic Systems
Most AI pilots stall the moment they touch real regulated data. We build the production layer between the model and the business: agents, retrieval, evaluation, and runtime ops so AI ships into environments where audit, latency, and cost are non-negotiable.
Agent engineering & orchestration
- Multi-agent systems with LangGraph, CrewAI, and the Anthropic and OpenAI Agent SDKs
- Planning patterns (ReAct, plan-and-execute, reflection) with strict tool and function-call schemas
- Model cascades and routing with cost-aware fallback and latency budgets
- Human-in-the-loop approval gates for high-stakes clinical, financial, and regulatory actions
Retrieval & RAG
- Vector platforms: Pinecone, pgvector, Azure AI Search, Vertex AI Vector Search
- Grounded citations, multimodal RAG, and GraphRAG with Neo4j
Evaluation & observability
- Eval harnesses, LLM-as-judge graders, and golden-set regression suites
- Red-teaming for prompt injection, jailbreaks, and PII/PHI leakage
- Trace observability with LangSmith, Langfuse, and OpenTelemetry
Safety, governance & policy
- Programs aligned to NIST AI RMF, ISO/IEC 42001, EU AI Act, and FDA AI/ML guidance
- PII/PHI redaction, content filtering, and prompt-injection defenses at the gateway
- Model cards, decision logs, and audit-ready evidence pipelines
LLMOps & runtime
- Inference on Amazon Bedrock, Azure OpenAI, and Google Vertex AI; self-hosted with vLLM
- Prompt versioning, A/B routing, shadow deployments, and canary releases
- Fine-tuning (LoRA), distillation, and model-selection economics
Data Engineering & Governance
Your AI ambitions are constrained by your data foundation. We design and build governed lakehouse and warehouse platforms, and the lineage, contracts, and observability that make the stack trustworthy enough to feed regulated AI workloads.
Cloud data platforms
- Snowflake: warehouse design, Snowpark, Cortex AI, Iceberg tables
- Databricks: lakehouse, Unity Catalog, Delta Live Tables, MLflow, Mosaic AI
- Google Cloud: BigQuery (incl. BigQuery ML, Gemini in BigQuery), Dataplex, Dataflow, Pub/Sub, Vertex AI Feature Store
- AWS: Redshift, Athena, Glue, Lake Formation, EMR, Kinesis
- Azure: Microsoft Fabric, Synapse, Purview, Data Factory
Pipelines & transformation
- Streaming and CDC with Kafka, Pub/Sub, Kinesis, Debezium, Fivetran
- ELT with dbt and Airflow; contract-first, model-tested builds
- Open table formats: Apache Iceberg and Delta Lake
Governance & quality
- Catalogs and lineage: Collibra, Unity Catalog, Microsoft Purview, Dataplex, OpenLineage
- Quality and observability: Monte Carlo, Great Expectations, Soda
- Fine-grained access: column- and row-level security, dynamic masking, tokenization
- Data products and contracts under a data-mesh operating model
AI-ready data
- Feature stores on Databricks, Vertex AI, and SageMaker
- Vectorization pipelines with embedding-version migration
- Synthetic data and privacy-preserving anonymization for AI training
Legacy & regulated migration
- Migrations from Teradata, Oracle, SQL Server, and Informatica PowerCenter
- Strangler-fig migrations with parallel-run, reconciliation, and rollback
- Regulator-grade lineage attestation and validation packs
Cybersecurity & Compliance
Most security programs fail not because of the controls, but because they don’t know what they’re protecting. Every Versetal engagement starts with a continuously maintained picture of where sensitive data lives, then we build zero-trust, identity, detection, and continuous compliance on top. Engineering-led, audit-ready by design.
Data security & DSPM
- Sensitive-data discovery and classification: Varonis, BigID, Microsoft Purview, Wiz
- DLP, CASB, and SASE: Zscaler, Netskope, Palo Alto, Cloudflare
- Encryption at rest, in transit, and in use; BYOK and HSMs
Identity, access & zero trust
- IdP modernization: Microsoft Entra ID, Okta
- Privileged access with CyberArk and BeyondTrust; cloud JIT via Entra PIM and AWS Identity Center
- Zero-trust segmentation, workload identity, and service-mesh mTLS
- Identity Threat Detection & Response (ITDR)
Threat detection & SOC engineering
- SIEM: Microsoft Sentinel, Splunk, Google Chronicle
- SOAR: Cortex XSOAR, Tines, Splunk SOAR
- EDR/XDR: CrowdStrike, SentinelOne, Microsoft Defender
- Dark web monitoring
Vulnerability & posture
- CSPM/CWPP: Prisma Cloud, Microsoft Defender for Cloud
- Application security: Snyk, GitHub Advanced Security, Veracode
- Security awareness: KnowBe4
Offensive security & validation
- Penetration testing across network, web, API, cloud, OT, and AI/agent surfaces
- Pentest-as-a-Service
- Red and purple team exercises mapped to MITRE ATT&CK
- Tabletop exercises and incident-response readiness
GRC & continuous compliance
- HIPAA, HITRUST, GxP/21 CFR Part 11, SOC 2, NIST 800-53, PCI DSS 4.0, ISO 27001
- Continuous control monitoring with Versetal CyberScore©
- vCISO engagements and regulator-ready documentation
Cloud & Infrastructure Modernization
Cloud done for regulated environments, not generic landing zones lifted from a vendor template. We design and run Azure, AWS, and Google Cloud foundations plus the hybrid and edge architectures regulated workloads still need.
Multi-cloud landing zones
- Azure: Landing Zones, Cloud Adoption Framework, Defender for Cloud baseline
- AWS: Control Tower, multi-account strategy, Identity Center
- Google Cloud: organization design, Security Command Center, Assured Workloads
- Compliance-scoped tenants for HIPAA, HITRUST, GxP, PCI, and FedRAMP-aligned workloads
Platform engineering & IaC
- Terraform, Bicep, Pulumi, AWS CDK
- Policy-as-code: OPA, Azure Policy, AWS Config, GCP Org Policy
- GitOps with Argo CD and Flux; secrets management with HashiCorp Vault
Kubernetes & serverless
- Managed Kubernetes on AKS, EKS, and GKE
- Service mesh (Istio, Linkerd) and Gateway API with mTLS by default
- Serverless: AWS Lambda, Azure Functions, Google Cloud Run
Hybrid & edge
- Private connectivity: ExpressRoute, Direct Connect, Cloud Interconnect
- Azure Arc, AWS Outposts, Google Distributed Cloud
- GxP-compliant lab and industrial-edge architectures
FinOps & reliability
- FinOps practices: showback, chargeback, unit economics
- Reserved Instances, Savings Plans, Committed Use Discounts
- SRE: SLOs, error budgets, capacity modeling
Application Development & Integration
Applications built to be observed, tested, governed, and extended by AI. Custom product engineering, integration platforms, and legacy modernization with engineering practices that make every build a foundation for the next one, not a liability.
Product engineering
- TypeScript with React and Next.js
- Backend: Node.js, Python, Go, .NET
- Mobile: iOS (Swift), Android (Kotlin), React Native
APIs & integration
- REST, GraphQL, and gRPC with OpenAPI-first contracts
- Event streaming: Kafka, EventBridge, Pub/Sub, Azure Service Bus
- iPaaS: MuleSoft, Boomi, Workato
- Healthcare interoperability: HL7, FHIR, Epic, Oracle Health
ERP & CRM administration
- Salesforce: Sales Cloud, Service Cloud, and Experience Cloud; Flow, Apex, sandbox management
- HubSpot: Sales Hub, Marketing Hub, and Operations Hub administration; workflow automation, custom objects, pipeline configuration, and CRM data management
- Microsoft Dynamics 365: Sales, Customer Service, Finance, Supply Chain with Power Platform
- SAP: S/4HANA and ECC support, security and role design, master data
- Oracle NetSuite and Workday: administration and configuration
- ServiceNow: ITSM, ITOM, and CSM administration
- Veeva: CRM and Vault administration for life sciences and pharma; GxP validation support, regulatory content workflows, and user management for regulated environments
AI-native applications
- Agentic UX copilots, streaming responses, tool-use surfaces, citation patterns
- LLM gateways with policy enforcement, PII redaction, and prompt caching
- Evals embedded in the product for safe model upgrades
Legacy modernization
- Strangler-fig with change-data-capture for incremental migration
- Mainframe and AS/400 wrapper APIs
- Database migrations: Oracle to Postgres, SQL Server to Postgres
DevSecOps & platform engineering
- CI/CD on GitHub Actions, GitLab CI, and Azure DevOps
- Software supply chain: SBOM, Sigstore, SLSA
- Observability: OpenTelemetry, Datadog, Grafana
- Feature flags, canary, and blue/green deployments
Need ongoing operations to run what we build? See Versetal Services: Service Desk, Compliance, and 24×7 Managed Operations.
Pick the disciplines. We'll bring the team.
Most engagements blend two or three of these capabilities. Tell us the outcome you need and we’ll propose the team that maps to it.