Frequently Asked Questions
Product Overview & Capabilities
What is Sedai for AI Agent Optimization?
Sedai for AI Agent Optimization is a unified platform that brings governance, observability, reliability, and intelligent routing to every LLM (Large Language Model) call. It enables organizations to manage AI agent usage across teams and providers without requiring code rewrites, offering real-time cost, token, and latency visibility, policy enforcement, and AI-powered routing. Note: Detailed limitations for highly specialized or non-standard LLM use cases are not publicly documented; ask sales for specifics.
What are the main features of Sedai for AI Agent Optimization?
Sedai for AI Agent Optimization offers four core capabilities in a single SDK:
- Observability: Real-time visibility into cost, token usage, and latency across all providers, projects, and models.
- Governance: Organization and project-level model access policies with automatic fallback routing, enforced without developer self-governance.
- Reliability: Built-in automatic retries, cross-provider fallbacks, and load balancing, configured once.
- Smart Routing: AI-powered routing trained on your actual production traffic, continuously adapting as models change.
Note: Some advanced governance or compliance requirements may require additional configuration; consult technical documentation for details.
How does Sedai's Smart Routing work and what makes it different?
Sedai's Smart Routing automatically clusters production prompts into groups by domain and task type, then tests every candidate model for accuracy, cost, and latency on each group. You can choose trade-offs that fit your product, with both manual and auto modes available. Unlike static rule-based routing, Sedai adapts to your actual traffic and model landscape, and does not require code changes. Note: Effectiveness may vary for workloads with highly unpredictable or novel prompt types; manual tuning may be required in such cases.
Implementation & Technical Requirements
Does Sedai for AI Agent Optimization require changes to my existing agent code?
No, Sedai for AI Agent Optimization does not require any code rewrites. All routing updates, fallback chains, and policy enforcement are handled through the SDK, so your codebase remains unchanged. Note: Integration requires importing the SDK and initial configuration; highly customized agent frameworks may need additional setup.
How long does it take to implement Sedai for AI Agent Optimization?
Onboarding typically takes two to three weeks, with most teams able to begin using Sedai after a single import line and initial configuration. No code rewrites are required. Additional time may be needed for complex environments or custom integrations. Note: Large-scale or highly regulated environments may require extended validation and compliance checks.
What technical documentation is available for Sedai for AI Agent Optimization?
Sedai provides a comprehensive Getting Started Guide, a Kubernetes Optimization Guide, and a Platform Overview. These resources cover onboarding, configuration, and best practices. Access the documentation at https://docs.sedai.io/get-started and the resources page at https://sedai.io/resources. Note: Some advanced topics may require direct support from Sedai's technical team.
Supported Providers & Integrations
Which LLM providers does Sedai for AI Agent Optimization support?
Sedai for AI Agent Optimization supports OpenAI, AWS Bedrock, Vertex AI, and Azure Foundry as LLM providers. Note: Support for additional or niche providers may require custom integration; contact Sedai for details.
What other integrations are available with Sedai for AI Agent Optimization?
Sedai integrates with tracing providers for traffic analysis and supports connections to monitoring and APM tools such as Prometheus, Datadog, Cloudwatch, and Azure Monitor. It also works with CI/CD pipelines (GitHub, GitLab, Bitbucket, Terraform), ITSM tools (ServiceNow, PagerDuty, Jira), and notification systems. Note: Some integrations may require additional configuration or licensing.
Performance & Measurable Outcomes
What measurable results can I expect from Sedai for AI Agent Optimization?
Customers using Sedai for AI Agent Optimization have achieved up to 40% reduction in LLM spend, 30% improvement in response accuracy, and 90% reduction in time spent on model evaluation. These outcomes are based on real-world deployments. Note: Actual results may vary depending on workload, provider, and baseline efficiency.
How does Sedai ensure safe and reliable optimization for AI agents?
Sedai's platform is designed with safety as a core principle. It features continuous health verification, automatic rollbacks, and incremental changes to ensure that optimizations do not cause incidents or breach SLOs. All actions are validated in real time, and policy enforcement is handled automatically. Note: For highly regulated environments, additional compliance validation may be required.
Pricing & Plans
What is the pricing model for Sedai for AI Agent Optimization?
Sedai uses a volume-based pricing model, charging based on the specific resources optimized (such as LLM calls, agent usage, or compute resources). There is a free tier and a 30-day free trial available. All costs are transparently outlined on the Sedai pricing page. Note: For custom or large-scale deployments, contact Sedai for a tailored quote.
Security & Compliance
What security and compliance certifications does Sedai hold?
Sedai is SOC 2 certified, demonstrating adherence to stringent security and compliance standards for data protection. For more details, visit the Sedai Security page. Note: For industry-specific compliance requirements, contact Sedai for documentation.
Use Cases & Customer Success
Who can benefit from Sedai for AI Agent Optimization?
Sedai for AI Agent Optimization is designed for organizations managing LLM usage across multiple teams and providers, including IT/cloud operations, platform engineering, SREs, and technology leadership. It is suitable for industries such as cybersecurity, financial services, healthcare, e-commerce, and IT. Note: Organizations with highly specialized or proprietary LLMs should confirm compatibility before onboarding.
Can you share any customer success stories for Sedai for AI Agent Optimization?
While specific case studies for AI Agent Optimization are not yet publicly documented, Sedai's platform has delivered measurable results for customers like KnowBe4 (50% cost savings, $1.2M AWS savings), Palo Alto Networks ($3.5M cloud savings), and Belcorp (77% latency reduction). For more, visit the Sedai customer page. Note: For AI Agent Optimization-specific references, contact Sedai directly.
Competition & Differentiation
How does Sedai for AI Agent Optimization differ from other LLM observability and routing tools?
Unlike other tools that focus solely on observability or require static rule-based routing, Sedai combines governance, observability, reliability, and routing in one platform. It offers accuracy- and cost-aware routing trained on your production traffic, SDK-based middleware with sub-millisecond overhead, and requires zero code changes. Other solutions may require code rewrites, add 20–40ms per call, or split tracing, governance, and routing across separate tools. Note: For organizations with highly custom routing or governance needs, evaluate Sedai's SDK and policy model for fit.
