What we have observed building AI agent systems inside banks, consumer enterprises, and operational organizations. A working record, updated as the work continues.
Actioneer and Kore.ai solve different enterprise AI problems. Kore.ai automates conversations. Actioneer answers business questions from structured data with 95.8% benchmark accuracy.
Actioneer's role-separated AI harness achieves 78.8% on KramaBench and 95.8% on DABstep at 40% lower cost per correct answer than monolithic frontier deployment. How harness design beats model scale.
The build vs buy AI platform decision for a medium sized company sits at a different point on the complexity curve than the equivalent decision at a large enterprise. Shared engineering teams, multi-source data stacks, and business timelines that cannot absorb 9-month infrastructure waits all s…
Every B2B AI startup promises a context layer that knows what your company knows. But retrieval is not authority. The real context layer is the one that helps an agent tell memory from evidence, narrated company from operating company, intention from receipt.
Deploying AI on confidential data does not require sending that data outside your infrastructure. Actioneer's on-premise and private deployment options keep all processing within organizational boundaries - with fully auditable outputs traceable to their source query, and a compliance posture b…
Why most enterprise AI builds fail to reach production. The build vs buy decision for AI data intelligence: four to nine months internal vs weeks with the right platform.
