Kore.ai vs Sierra (2026)

The tools and integrations layer connects outside systems over HTTP, MCP, AWS Lambda, SDK invocations, the A2A protocol, sandboxed tools, OpenAPI definitions and webhooks, with circuit breakers and retry logic. Data sources such as Salesforce, SAP, Microsoft, VMware and Zendesk are reached through tool definitions, so none of them is built into agent logic.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Agents reach the customer's systems of record to carry out end to end transactions, including card and ACH payments, returns, authentication and cancellation saves, and those system interactions are held deterministic and bound by policy. Agent Studio offers ready integrations and an integration framework for proprietary systems, and the Agent SDK builds the rest, so the range of connected systems depends on what each team sets up. Integrations also route a conversation to the customer's care team with its full context.

Sourcesierra.ai/product/agent-sdkread 2026-09-05

Four orchestration patterns are invoked through ABL constructs and enforced by the runtime. They include parallel fan out with barrier synchronization, asynchronous delegation that survives pod restarts, and turns carrying several intents that map to several agents.

Supervisor routing arbitrates handoff and delegation, a pipeline classifier skips the reasoning loop for intents it recognizes with high confidence, and the Google A2A protocol carries communication to agents hosted on other runtimes. The runtime's two engines execute agentic reasoning and deterministic flows in parallel from one definition.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Agents are put together from skills such as triage, respond and confirm, combined into multistep workflows for a specific use case. In Agent Studio a team defines those journeys step by step or has AI generate them from its existing operating procedures, and Ghostwriter builds or changes an agent from a description of how it should behave. Flexibility is set per workflow, so a team can move between deterministic execution and open ended reasoning on the same agent.

Sourcesierra.ai/product/agent-sdkread 2026-09-05

Agents deploy across 27 channels covering web, voice, messaging, email and enterprise APIs, among them Microsoft Teams, ServiceNow, Slack, Webex and Zoom, with consistent behavior and no rebuilding for each channel.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

An agent is built once and deployed across chat, phone, email, SMS and messaging, with the same skills and policies applying on each. A single agent working across every channel is the core idea of the platform.

Sourcesierra.ai/product/agent-sdkread 2026-09-05

Search AI is the platform's knowledge retrieval layer, providing RAG, vector search, knowledge graph traversal and reranking to surface context to agents as they reason. The customer configures it and the platform maintains it, and the retrieval pipeline comes with guidance on model selection, chunking and context window sizing.

SourceKore.ai Agent Platform and Search AI documentation; docs.kore.ai/agent-platformread 2026-09-05

Agents ground answers in the customer's own content through retrieval built into Agent OS, and the Agent Data Platform joins that knowledge with customer context from other systems. In Agent Studio a team connects its knowledge sources and views and edits help center content, FAQs and policies. Sierra spots common themes missing from the knowledge base and drafts new articles from how care representatives resolved edge cases, so the store grows without manual updates.

Sourcesierra.ai/product/agent-sdkread 2026-09-05

Memory is a formal construct in Agent Blueprint Language alongside goals, tools and guardrails, executed against a shared memory layer that coordinates state across both cognitive engines. Session Meta Memory is managed by the system.

Custom Memory Stores are persistent and structured with JSON Schema, and each takes a scope: one user across all of that user's sessions, a single session that clears when it ends, or the whole application. A retention policy sets each store to last a session, a day, a week or a month, and tools read, write and delete store content at run time. Shared stores pass structured context between agents.

Sourcedocs.kore.ai agent platform memory stores guideread 2026-10-25

Agents personalize each conversation from agent memory and the customer's profile, and the Agent Data Platform brings together what the agent knows about a specific customer across sessions, channels and systems, so context carries from one conversation to the next. How long that memory lasts, and whether a customer's record of it can be viewed or cleared, is not public.

Sourcesierra.ai/product/insightsread 2026-09-05

The Workflow Engine runs workflows lasting minutes to days, with built in steps where a person reviews the work and approval gates that hold it until someone signs off. Guardrails are a core ABL construct enforced outside the model, the runtime carries guardrails in several tiers with circuit breakers and rate limits, and supervisor routing checks those guardrails, so the runtime overrides an agent's chosen route when policy requires. Arch AI hands its work products to a person to review and never applies them silently.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Sierra wraps its models in supervisory layers that check outputs against scope and policy before the agent responds, to reduce hallucination and prevent abuse. Access to systems of record is deterministic and controlled, and the customer's policies and security procedures are enforced outside the model. Flexibility settings on each workflow limit how far the agent may improvise.

Sourcesierra.ai/product/trust-and-reliabilityread 2026-09-05

Security and governance include SSO, role based access control, guardrails, audit logging, encryption, key management, multitenancy with full tenant isolation, PII detection, identity verification and compliance reporting, on an enterprise foundation carrying PCI, SOC 2, GDPR and FedRAMP certification, with handling for the right to erasure and data minimization controls.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Sierra holds ISO/IEC 27001:2022 and ISO/IEC 42001:2023 certificates, a SOC 2 Type II report, a HIPAA attestation for 2026 and PCI DSS Level 1 service provider certification. Its trust center also covers the European and California privacy laws, the CSA STAR registry and FedRAMP High, with controls and policies shared on request.

Personal information shared with an agent is encrypted and masked automatically, filters block topics and keywords a company puts off limits, and cardholder data runs on dedicated PCI infrastructure that never touches Sierra's core platform, models or storage. Customer data is never used to train models or shared with other customers. Who inside a customer's own organization can build, edit or publish an agent, through single sign on, roles or permissions, is not public.

Sourcesierra.ai/product/trust-and-reliabilityread 2026-09-05

Observability follows the agent's reasoning, capturing every reasoning step, tool call, routing decision and guardrail evaluation as structured trace data across chains of delegated agents. Deep Observability records over 200 trace events per session and provides runtime inspection, alerting and debugging of each session across interactions between agents.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Every agent action can be traced to its reasoning, with the knowledge sources and systems it used, and developers inspect API calls and logic traces while Agent Studio shows a live trace of each decision, tool call and response during a build.

Insights reports on CSAT, resolution and other metrics with custom reports, tags and categorizes conversations automatically, flags the ones that need a person's attention and sends alerts on abuse attempts or performance drops to a team's existing tools.

Explorer answers questions about thousands of conversations with themes, data and links to the conversations behind each finding, and delivers a weekly briefing on its own.

Sourcesierra.ai/product/insightsread 2026-09-05

Kore.ai runs as cloud SaaS or self hosted for organizations with data residency or compliance requirements, with the same platform capabilities either way. The infrastructure layer plugs into Microsoft Azure, Google Cloud, AWS, on premises installations and private VPC deployments, so the customer chooses where the platform runs.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Sierra hosts the platform as SaaS. Each subprocessor carries its own processing location on the trust center, and customers do not pick a region. There is no VPC, single tenant or on premises option. The FedRAMP High commitment points to separate government infrastructure, though no choice of residency regions is offered.

Sourcesierra.ai/product/trust-and-reliabilityread 2026-09-05

The AI agent marketplace offers named prebuilt agents across banking (ATM Locator, Dispute and Fraud Handler), retail (Product Search, Order Management), HR (Absence Management, Screening Agent), IT (Incident Management, Access Management), sales (RFP Response Automation, Lead Analyzer), legal and finance (Contract Amendment Assistant) and customer service (Escalation Predictor, Contextual Email Responder), installed with one click. Marketplace agents import with their predefined tools and workflows, and any component can be edited afterwards.

SourceKore.ai AI agent marketplace and Create an Agent from Marketplace documentation; docs.kore.ai/agent-platform/agents/create-from-marketplaceread 2026-09-30

The Agent SDK ships with a range of AI skills and systems integrations to help customers go live faster, and skills such as triage, respond and confirm work as reusable building blocks. Customers assemble these pieces themselves. There are no named prebuilt agents, templates, library or marketplace.

Sourcesierra.ai/product/agent-sdkread 2026-09-05

Every layer of the ecosystem is pluggable, so the customer swaps providers without rewriting agents. Supported models include OpenAI, Anthropic, NVIDIA, Cohere and LLaMA 2 among others, and open source and custom fine tuned models work through the same interface. A models library lets an admin add a new model or a custom integration, models hosted by a third party or by the enterprise itself can be brought in, each feature can be assigned its own model, and an analytics dashboard reports token distribution, latency and cost per model connection.

SourceKore.ai Agent Platform and Generative AI model documentation; docs.kore.ai/agent-platformread 2026-09-05

Agents draw on more than fifteen frontier, open weight and proprietary models chosen per job, and Sierra switches between LLM providers automatically to optimize performance and keep running during a provider outage. Model serving runs through subprocessors that include Anthropic, Google, AWS, Baseten, Fireworks AI, Together AI and Modal. Routing happens inside Sierra, and neither customers nor admins choose the model.

Sourcesierra.ai/blog/constellation-of-modelsread 2026-09-05

Agent Blueprint Language is a typed language driven by schemas, compiled from DSL to intermediate representation to runtime, with definitions stored in Git as diffable YAML, reviewed in pull requests and promoted by the same CI/CD practices as application code. The tools layer exposes HTTP, MCP, SDK invocations, OpenAPI, webhooks and the A2A protocol for communication with agents on other runtimes, including agents hosted outside the platform.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Developers build, customize and deploy agents with the Agent SDK, which comes with documentation, interactive training and a development pipeline. Agent OS adds ready made tooling for building, deploying and managing agents. There is no public API reference or MCP server for the platform itself, so developers work through the SDK.

Sourcesierra.ai/product/agent-sdkread 2026-09-05

Agent Evals is an automated evaluation framework for the customer's own agents, with test suites, regression tracking and quality gates that run as part of the deployment pipeline, and the results decide whether an agent is promoted. The environment pipeline routes every agent through a staging tier where automated suites and regression checks run before a pilot tier validates behavior on limited real traffic. Validation at compile time catches broken references before deployment.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Agent Studio simulates conversations and scores the agent against defined outcomes, and a team builds a regression test suite that runs before each new version of the agent is released.

Voice agents are tested for transcription, background noise and speaker variation before going live, and the Agent SDK checks behavior across a wide range of scenarios in a development pipeline, so definitions are not edited live.

After launch, Insights runs experiments on variations of agent behavior such as handoff rules or levels of determinism, and Explorer compares performance before and after a change Ghostwriter has made.

Sourcesierra.ai/product/agent-studioread 2026-09-05

Agents reach outside systems only through the tools layer (HTTP, MCP, Lambda, SDK, A2A, OpenAPI and webhooks) and reach users through 27 programmatic channels. They do not drive a browser, a virtual desktop or software that lacks a programmatic interface.

SourceKore.ai Agent Platform documentation; docs.kore.ai/agent-platformread 2026-09-05

Agents act on the customer's systems through API integrations built with the SDK, kept deterministic and bound by policy, and deploy across chat, phone, email, SMS and messaging. Browser control, a virtual desktop and operation of software without a programmatic interface are not part of the platform.

Sourcesierra.ai/product/agent-sdkread 2026-09-05