Deploy secure, autonomous agents at scale
A full-stack solution built to deploy intelligent agents that are secure, explainable, and optimized for your specific tasks or industries.
Scale AI with agents you can trust
Deliver outcomes with secure, auditable, and customizable agents, built for enterprise-grade performance and compliance.
Built-in observability
Track every tool call, decision, and output for full transparency and debugging.
Structured outputs
Return schema-validated data ready for direct integration into your systems.
Ring-fenced execution
Run agents in controlled environments that safeguard data and prevent drift.
Tailored domain
Adapt agents to specialized workflows, regulatory needs, and industry tasks.
Enterprise reliability
Deploy at scale with consistent performance, auditability, and governance.
Custom tools
Extend agent logic with APIs and functions that plug directly into your stack.
Agent capabilities
How SeekrFlow™ Agents work
Each agent follows a reasoning loop that ensures clarity, control, and adaptability, making autonomous systems reliable for enterprise use.
Agents map the path before acting
The agent begins by interpreting the user’s goal and generating a step-by-step plan to achieve it. This includes identifying intermediate steps, deciding which tools to use, and defining expected outcomes. By separating reasoning from execution, SeekrFlow Agents ensure every action is deliberate, auditable, and aligned with the task at hand.
Critical review before execution
Before taking action, the agent reviews and refines its plan. It critiques the proposed steps, validates logical soundness, and makes adjustments if needed. This reflection stage prevents wasted computation and enables human-in-the-loop oversight where required.
Controlled execution with observability
With a validated plan, the agent proceeds to execute step by step. It orchestrates selected tools, invokes base or fine-tuned models, and adapts in real time based on outputs or user feedback. Each tool call runs in a ring-fenced environment to protect data and maintain control.
Secure by design
With Seekr, your data remains yours. We never use it to train other models and give you full control to install our platform wherever your data resides. Our SOC 2 certification ensures best-in-class security, featuring fine-grained access controls and the flexibility to run on your preferred cloud or hardware.
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more accurate model responses
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more relevance in responses
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faster to prepare a dataset vs. others
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cheaper costs vs traditional approaches
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minutes or less to build a production-grade LLM
Top enterprise and government leaders trust Seekr
“Seekr is setting a high bar for performant and efficient end-to-end AI development with its SeekrFlow platform, powered by AMD Instinct MI300X GPUs. We’re proud to work with Seekr as they showcase what’s possible using AMD Instinct GPUs on OCI’s AI enterprise infrastructure.”
Negin Oliver
CVP, Business Development – AI and Cloud at AMD
Latest insights
View all resources
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New in SeekrFlow™ Agents: Structured Outputs, Custom Tools, and Validated Functions
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Black Box to Open Book: How Citation-Based Agents Build Trust
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Introducing SeekrFlow™ Agents: Deploy intelligent AI that thinks, plans, and acts with accuracy and control
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Putting AI Agents to Work: Top Enterprise Use Cases to Start Building Now
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Understanding AI Agents: The Next Step in Enterprise Transformation
FAQs
How do agents maintain context?
Agents use threads to store all messages, ensuring context persists across interactions and can be audited later.
Can I define custom tools?
Yes. Developers can build custom tools with APIs or SDKs. Each runs in a secure, ring-fenced environment.
How are outputs validated?
Agents return schema-validated outputs (JSON, Pydantic models) to guarantee predictable, integration-ready results.
How is agent execution observed?
The Observability Platform logs every decision, tool call, and output, enabling debugging, compliance, and audits.
Can humans review decisions?
Yes. A human-in-the-loop can be introduced at the plan evaluation stage or before execution in sensitive workflows.
How is security enforced?
All tool calls and data handling occur in ring-fenced environments, preventing drift and protecting sensitive inputs.
Do agents adapt in real time?
Yes. Agents adjust their plans dynamically based on tool outputs, user feedback, or updated context.
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