Platformatory
Consulting
AI is more than frontier-model wrappers. We ship agents with a deterministic core, an agentic shell, and autonomy & accuracy SLOs that move together.
Surfaces
Short labels for how we engage. The how-we-build detail is below.
Multi-agent plans that tool-call, hand off, and recover across real business processes—executed durably, because MCP tool calls fail.
In-harness assistants and eval loops: sandboxes, continuous eval & improvement, and runtime guardrails that keep agents steerable.
Domain-specific models—RL’d, fine-tuned, and distilled—where control, cost, and tokens matter more than the biggest frontier wrapper.
Enterprise tools as first-class agent interfaces. Often the win is good tools for in-harness use—not another self-branded agent.
How we build
The secret sauce is not a thicker wrapper around a frontier model. It is a deterministic core with an agentic shell: durable workflows, authorization policies for agent principals, audit trails, and bounded hallucinations—because most models are still stochastic parrots.
Two archetypes show up again and again: in-harness assistants, and agentic workflows. There is overlap. Both need continuous eval. ROI often comes through RL—models that are RL’d, fine-tuned, and distilled outperform on cost and tokens. Domain-specific models rise; the self-branded agent is optional.
We have built on the order of two dozen agents and shipped them into production—retail, surveillance, supply chain and control-tower operations, fund operations, and more. For OSS / BYOM agents in the portfolio, start with the Write Ahead Log; a dedicated portfolio page comes later.
Next step
Bring the workflow, the autonomy you want, and the accuracy you cannot give up. We will say when a harness, a workflow, or just better tools is the right move.
