A platform that designs, deploys, and monitors AI agents inside enterprise workflows across systems like Salesforce, SAP, and Workday.
Added Jun 4, 2026
Last signal 1d ago
Enterprises are trying to turn AI agents from prototypes into production systems that actually operate within complex customer and employee workflows. The postings repeatedly point to custom integration, workflow redesign, and production readiness as hard problems that currently require forward deployed engineers, solution engineers, and technical delivery teams.
AgentFlow would provide a workflow orchestration layer for mapping business processes, connecting enterprise systems, deploying agent actions, and monitoring outcomes. It would include templates for common enterprise workflows, approval gates for human-in-the-loop execution, and observability for agent performance across customer ecosystems.
Companies are actively hiring teams to build agentic workflows directly with customers, suggesting demand has moved beyond experimentation into deployment. The rise of multi-agent systems and enterprise AI platforms creates urgency for tooling that makes these workflows scalable and reliable.
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* Build multi‑step agent pipelines that combine rules, ML models, and reasoning components to solve complex business problems. * Integrate agentic systems with enterprise data, ML models, and applications to enable intelligent automation and decision support.
Hey PH 👋 I started Graft after realizing that the hardest part of deploying agents at work is not the model. It is the software around it. Real companies run on ERPs, desktop apps, internal portals, spreadsheets, and years of operational knowledge that agents cannot reliably understand or use. Graft began as a way to turn those interfaces into stable tools for agents. While building it, the idea grew into something bigger: a living map of how a company actually works. Graft learns the workflow, decisions, permissions, exceptions, and success conditions, then gives agents a safe way to do the work with approvals, audit trails, and verification built in. When the underlying software changes, the agent-facing tool stays stable. We are launching early because we want to learn from the people actually building and operating agents. What is one system or workflow your agent still cannot reliably use today?
Graft will be helping f500's transform their legacy applications into operational knowledge basis for agents to use. Agents can interact with their legacy software and help them transition into agent native software, this is a shift we're seeing but companies fail because the data is in people's head as domain knowledge so we're building the infra to make it operational by agents.
Identify opportunities for Generative AI, Agentic AI, and workflow orchestration Design end-to-end integrations across SAP, Ariba, UiPath, Microsoft Power Platform, and AI platforms
Architect and implement intelligent, multi-agent workflow ecosystems that enable autonomous decision-making, orchestration, and coordination across complex business processes. Develop reusable playbooks, frameworks, and reference architectures that guide teams in designing, developing, and deploying AI-driven workflows efficiently.
You will work with customers across the Americas to design and implement production-intent solutions on SAP Business AI Platform, with a focus on AI-enabled scenarios including custom agents, intelligent applications, and intelligent workflows such as n8n. Through hands-on development, you will help transform emerging SAP capabilities into real, working solutions for customer use cases.
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