# Field Runtime

> Field Runtime is a Pacific Northwest forward-deployed AI engineering company that helps enterprises design, deploy, govern, evaluate, and improve agentic systems inside real workflows.

Field Runtime works with CIOs, operating leaders, and enterprise teams. We begin with one consequential workflow, establish its economics and human authority, build the governed system around the work, and transfer an evidence-driven learning loop to the organization.

## Core services

- [Field Discovery Sprint](https://fieldruntime.ai/field-discovery-sprint): A fixed-scope, two-to-three-week engagement for one consequential workflow. Produces the workflow evidence map, economic baseline, intelligence supply-chain plan, human and economic authority contract, context-exposure limits, provider failover, proprietary eval plan, provenance requirements, outcome ledger, runtime architecture, and a build, buy, redesign, or stop recommendation.
- [How Field Runtime works](https://fieldruntime.ai/how-we-work): Field Discovery, System Delivery, Team Ownership, and Learning Operations.
- [Enterprise agentic systems](https://fieldruntime.ai/agentic-systems): Context, harnesses, agent runtimes, controlled tools, evaluations, governance, and human authority.
- [Enterprise AI agent deployment](https://fieldruntime.ai/enterprise-ai-agent-deployment): A CIO guide from workflow economics and production architecture through real-task evaluations, bounded launch, ownership, and learning operations.
- [Enterprise AI guides](https://fieldruntime.ai/guides): CIO and CFO decision frameworks for evaluating, funding, deploying, governing, measuring, and improving consequential AI workflows.
- [AI production readiness](https://fieldruntime.ai/ai-production-readiness): A CIO evaluation framework covering value, workflow legibility, context, evaluation, authority, operability, ownership, and learning.
- [Build vs. Buy Enterprise AI](https://fieldruntime.ai/build-vs-buy-enterprise-ai): A CIO–CFO decision framework for choosing whether to buy, configure, compose, build, or retire software around one consequential workflow.
- [Deployment blueprints](https://fieldruntime.ai/deployment-blueprints): Revenue, finance, customer-support, and technical-operations workflow patterns.
- [Measurement cases](https://fieldruntime.ai/case-studies): Transparent enterprise AI outcome models with assumptions, formulas, controls, and evidence plans. These are modeled cases, not client-result claims.
- [AI Production Readiness Check](https://fieldruntime.ai/survey): A seven-minute assessment for one real enterprise AI workflow.
- [Map a workflow](https://fieldruntime.ai/map-a-workflow): Start a Field Discovery conversation.

## Key ideas

- The agent is one worker inside a governed workflow system; the agent is not the product.
- Models supply intelligence. The surrounding runtime supplies context, state, tools, permissions, approvals, verification, memory, and learning.
- Enterprises should own the policy that determines which work is local, cached, specialist, or frontier; provider choice should remain replaceable.
- AI automates tasks while people retain authority over goals, relationships, material risk, novel exceptions, and system change.
- Production outcomes, failures, exceptions, and human corrections should become reviewed, tested, versioned, and reversible improvements.
- The smallest workflow that measurably improves an outcome is the right place to begin.

## Field Notes

Field Notes are authored by Mehtap Mae Ozkan, founder of Field Runtime.

- [The Enterprise Bottleneck Is Learning Throughput](https://fieldruntime.ai/insights/the-enterprise-bottleneck-is-learning-throughput)
- [When Judgment Becomes Executable](https://fieldruntime.ai/insights/when-judgment-becomes-executable)
- [Knowing When to Stop: The Art of Making a Loop Converge](https://fieldruntime.ai/insights/knowing-when-to-stop)
- [Agent Security Must Move From Process to Technical Controls](https://fieldruntime.ai/insights/agent-security-technical-controls)
- [Why Enterprise Agents Need Operational CI](https://fieldruntime.ai/insights/why-enterprise-agents-need-operational-ci)
- [The Harness Is Where the Company Learns](https://fieldruntime.ai/insights/the-harness-is-where-the-company-learns)
- [A Company Brain Is Not Enough](https://fieldruntime.ai/insights/a-company-brain-is-not-enough)
- [The Model Is Not the Deployment](https://fieldruntime.ai/insights/the-model-is-not-the-deployment)
- [The Company That Knows What to Do Next](https://fieldruntime.ai/insights/the-company-that-knows-what-to-do-next)
- [The Company Is Not a Brain. It Is a School.](https://fieldruntime.ai/insights/the-company-is-a-school)
- [The Model Is Not the Product](https://fieldruntime.ai/insights/the-model-is-not-the-product)
- [The Operating Threshold](https://fieldruntime.ai/insights/agentic-enterprise-operating-threshold)
- [Graph Engineering: 10 Rules for Enterprise AI That Works](https://fieldruntime.ai/insights/graph-engineering-rules)
- [Build the Operating System Around the Work](https://fieldruntime.ai/insights/workflow-operating-systems)
- [All Insights](https://fieldruntime.ai/insights)

## Measurement cases

- [Revenue operations](https://fieldruntime.ai/case-studies/revenue-operations): Seller capacity, pricing-approval cycle time, CRM completeness, and deal-preparation quality.
- [Finance operations](https://fieldruntime.ai/case-studies/finance-operations): Exception capacity, close readiness, transaction rework, and evidence completeness.
- [Customer support](https://fieldruntime.ai/case-studies/customer-support): Support capacity, response time, resolution time, and reopened cases.
- All values are example assumptions. Field Discovery replaces them with verified operating data before an enterprise business case is approved.

## Company

- [About Field Runtime and the Field Runners](https://fieldruntime.ai/about)
- Founder: Mehtap Mae Ozkan
- Based in the Pacific Northwest; works with enterprise teams across the United States.
- Contact: mae@fieldruntime.ai

## More detail

- [Full machine-readable company and content guide](https://fieldruntime.ai/llms-full.txt)
- [RSS feed](https://fieldruntime.ai/feed.xml)
- [XML sitemap](https://fieldruntime.ai/sitemap.xml)