Four practices, one engineering bar.
ADILABS works in four practice areas. They share one delivery model — senior teams, end-to-end ownership, production discipline. Every label below is something we have taken to production for a paying customer.
Agents that ship to production — and stay there.
We engineer agentic systems on the same frameworks the platform vendors are betting on, with the user-aware permissioning, evaluation, and observability that make them safe to ship into enterprise environments. Plus the adoption work to roll Microsoft Copilot — and custom Copilots — across an organization.
Multi-agent systems on Microsoft Agent Framework, LangGraph, CrewAI. Tools exposed via MCP, agent-to-agent over A2A, streaming UX over AG-UI.
Hybrid lexical + vector retrieval, metadata-aware filters, graph memory for long-running cases. Source-grounded answers with citations.
Microsoft 365 Copilot rollouts, custom Copilot apps for line-of-business workflows, Microsoft Graph + Dataverse integrations, tenant-level governance.
- User-aware agents — agents inherit your RBAC at function-call time
- Audit trails, replay, structured responses on every run
- Evaluation harnesses and policy regressions in CI
- Microsoft 365 Copilot rollout playbooks with DLP
- Custom Copilot applications for Outlook, Teams, SharePoint
Software your operations run on.
End-to-end product engineering for the office and the field — planning, EVM, forecasting, daily reporting, progressive billing, mobile capture with offline sync. We don't hand over a prototype and walk away; we run these products in production and stand behind them.
Web platforms covering planning, cost-breakdown structures, purchase orders, daily reports, progressive billing, EVM and forecasting. Industrial-strength workflows, not dashboards.
iOS and Android apps that survive on a job site — offline-first sync, photo capture, signatures, role-aware data entry. Built on React Native or Flutter with PowerSync.
Architecture through go-live and beyond. We host environments on your behalf, or hand over to your internal IT team when they're ready — your call.
- Office and field products that scale to enterprise alliances and divisions
- Progressive Billing Applications and EVM modules with industry-standard graphs (EAC, ETC, etc.)
- Offline-capable mobile with conflict-aware sync
- Role-based access, audit logs, and reporting end-to-end
- Hosted-on-behalf operations or full handover to internal IT
From legacy ETL to lakehouse, without breaking what works.
We modernize data estates that other teams have been afraid to touch. Informatica to AWS Glue. On-prem warehouses to Synapse and Databricks. Bespoke integrations across SAP, Tulip, Salesforce, and the systems that quietly run your business.
Migrations and net-new builds on AWS Glue + Spark, Azure Synapse, Data Factory, Databricks, Delta Lake. Real pipelines, real cost discipline.
MuleSoft engines wired into SAP, Tulip, and bespoke systems. Power Platform integrations across Power Apps, Power Automate, and Dataverse.
We ran the Eli Lilly Informatica → AWS Glue migration end-to-end. Full pipeline rewrite, parallel-run validation, on-time go-live.
- Pipeline-by-pipeline migrations from legacy ETL to cloud-native
- Lakehouse architectures with governance and cost guardrails
- MuleSoft integration platforms and bespoke connectors
- Power Platform applications with Dataverse data models
- Architecture reviews and roadmaps for executive stakeholders
A real SRE practice — not a DevOps engineer with a Helm chart.
Software is only as good as the platform it runs on. Our SRE team designs CNCF-native platforms, runs them with GitOps, and instruments them end-to-end. It's how we host 30+ production environments today, and how we hand over a platform that your IT team can actually operate.
CNCF-native. Multi-tenant clusters, network policy, secret management, certificate rotation. The boring stuff, done right.
Flux and Argo for continuous delivery. Prometheus and Grafana for metrics. Logs and traces aggregated and queryable.
SLOs, error budgets, capacity and cost reviews. We run on-call rotations on the systems we operate, and write the runbooks for the ones we hand over.
- Production-grade Kubernetes platforms on AWS or Azure
- GitOps-driven delivery with progressive rollouts
- Observability stacks with SLOs and alerting
- Hosted operations with on-call coverage
- Handover packages — runbooks, dashboards, training — to internal IT