ASMBL Agentics
Large consultancies run enterprise-wide programs. We’re built for companies that need AI shipped fast, by the team that builds it. We’re strongest in hands-on software delivery, regulated environments like healthcare, and software companies whose own products need to become AI-native.
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ASMBL Ignition
Built for CEOs and leadership teams. The diagnostic covers use case opportunities, integration with systems of record, and data readiness, so every recommendation reflects what can be built on the client’s current foundation. Where leadership needs it, we also define the AI operating model: who owns AI decisions, how use cases get prioritized and funded, and how governance works in practice.
Claude-Powered Workflow / Agent Orchestration
Two tracks under one offering. Internal workflows serve operations leaders. Customer-facing products serve product and business owners. Every build connects to the client’s systems of record and ships with an evaluation harness, so quality is measured from day one. For software companies, this includes making their own products agent-ready.
AI-Native Engineering
Engineering transformation.
We set up Claude across the full development lifecycle, with your architecture rules, coding standards, security boundaries, and review gates encoded into how the agents work. We measure the productivity impact so you’re not guessing.
Legacy modernization.
Migrating a monolith, upgrading an aging framework, retiring a platform nobody wants to touch. Claude-assisted modernization changes the economics of work companies have deferred for years. It draws directly on fifteen years of ASMBL software delivery.
Managed AI Operations / FDE-as-a-Service
Most AI programs don’t fail at launch. They fail six months later, when adoption stalls and nobody owns the agents in production. We operate both sides of a client’s Claude estate.
For the workforce, we keep shared skills and connectors current, track adoption and value by department, and support internal champions. For agents in production, we monitor quality and drift, handle model upgrades, manage cost, maintain agent context, keep governance controls current, and report on business outcomes.