Not a plan. A measurement.
Comware is a 30-year enterprise AI/ML consulting firm. Like everyone else in this market, we have a story about becoming an "agent-native" business. Unlike the story most firms tell, ours started with instrumentation rather than ambition: over the last two months we logged how our work actually gets done.
The result was more specific than we expected. Our core production process — how we build and deliver software and AI for clients — is already agent-native. Across 23 of 54 recent projects, delivery ran through an agent-orchestrated pipeline: spec validation, planning, implementation, adversarial audit, and release, with humans at the gates that matter. Delivery is roughly 70% of our revenue. So the part of the firm that earns most of the money is the part that is demonstrably, measurably agent-native today.
That reframes the strategic question. We don't merely advise clients on agent-native transformation — we deliver inside one, and we can install the same pipeline in client organisations.
The production lineWhat the pipeline actually looks like
The most credible thing an AI consulting firm can show an enterprise buyer is not an automated back office — every competitor claims that. It's a production line that is faster, spec-correct, auditable by construction, and secured for client data. Click a stage:
Two numbers matter most. 876 subagent hand-offs — the work genuinely flows through agents, not around them. And 280 human checkpoints — judgment is engineered into the pipeline, not hoped for. The pipeline is auditable by construction: every release is certified against the spec it started from.
The moatAgents are table stakes. The methodology isn't.
The 152 generic agents in our ecosystem are not the moat — any competitor can install agents. The moat is the delivery methodology encoded into the pipeline and refined across real engagements: which gates exist, where humans sit, how adversarial audit works, what a certified release means. That is proprietary, battle-tested, and productizable.
This is what we sell as Agent-Native Delivery: we install our production line inside your organisation, with your governance, on your data boundaries.
The honest partWhat we haven't proven yet
Radical transparency cuts both ways, so here is what the evidence does not yet show. Advisory work (~30% of revenue) is not yet proven agent-native in instrumented tooling — partly because it happens in conversations the tools don't record, partly a genuine gap. It is the highest-value target for our next pilot, not delivery, which is already demonstrated.
The forward-looking business case rests on a productivity hypothesis that is not yet proven: the ROI projections, KPI targets, and the ~85%-of-workflows automation goal are estimates gated on measured pilot results — not commitments. Across our 14 capability pillars we score 78% target-state coverage (±10 points, a structured judgment rather than a measurement — the scoring method is documented), with 10 new agents to build across a three-month roadmap.
Everything — the roadmap, the risk register, the cost model, the full 152-agent roster — is in the blueprint. Unredacted.