Pyrana vs Amazon Bedrock AgentCore

Architecture

AgentCore and Pyrana solve different layers. AgentCore is a menu of managed AWS services that run, connect, secure, and measure agents, used together or one at a time. Pyrana is an application platform: identity, authorization, storage, orchestration, approvals, audit, and context built once, with each business application defined as configuration on top. AgentCore's unit is the agent. Pyrana's unit is the application.

AgentCore's services are Runtime (serverless microVMs or EC2-backed Instances), Harness, Memory, Gateway, Identity, Code Interpreter, Browser, Observability, Evaluations, Optimization, Policy, Payments, and Registry. Runtime accepts any framework, including Strands Agents, LangGraph, CrewAI, LlamaIndex, Google ADK, and the OpenAI Agents SDK, and supports MCP and A2A. AWS also positions AgentCore for building internal agent platforms: a paved path with approved tools, shared memory, and central authentication.

Pyrana's App configuration names an application's pages, operations, resources, agents, workflows, tool bindings, access profiles, and approval policies. Agents belong to an App and inherit its rules. Every call, from a page, the copilot, the API, MCP, a schedule, or an event, passes one eight-step gate.

What AgentCore launched in 2026

AgentCore has moved quickly, and much of it closes gaps teams used to fill themselves:

• Policy, GA March 2026. Deterministic rules for agent tool calls, intercepted at the Gateway, written in Cedar or natural language. Bedrock Guardrails support followed in July.
• Evaluations, GA March 2026. Thirteen built-in evaluators, ground-truth checks, and custom evaluators; batch evaluation and A/B testing went GA in July.
• Harness, GA July 2026. A managed agent loop defined by model, tools, skills, and instructions, with no orchestration code or container. Lifecycle hooks and interactive shells followed in September.
• Managed Knowledge Base, GA July 2026. A managed retrieval pipeline queried through the Gateway, with six connectors.
• AWS Agent Registry, GA August 2026. A catalog of agents, MCP servers, tools, and skills, with discovery across AWS Organizations accounts.
• Consent Portal, September 2026. A hosted page where end users approve an agent's access to resources on their behalf.

AgentCore also became SOC 1, 2, and 3 compliant in July 2026, and memory, policy, and harness reached AWS GovCloud (US-West) in August.

Context and knowledge

AgentCore remembers and retrieves. Pyrana curates knowledge as governed claims with evidence. AgentCore Memory provides short-term, long-term, and episodic memory, direct ingestion, and record time-to-live. Managed Knowledge Base adds hybrid search over S3, SharePoint, Confluence, Google Drive, OneDrive, and web content. Pyrana's context engine, cortIQ, stores knowledge as Context Units: a claim, its evidence passage, a type, a classification, and a content-hash identity.

The difference is governance of change and proof of use. In cortIQ, classification gates every change: absolute units never auto-change, regulated units wait for a person, tribal units are conflict-checked, and new units supersede old ones rather than overwrite them. Each run accounts for every unit as retrieved, injected, or cited, with content-addressed citations, so the business context behind an output is provable after the fact.

Agent capabilities

AgentCore offers more runtime choices. Pyrana offers more structure for agents working inside an application. AgentCore runs agent code in isolated microVM sessions, or defines agents through the Harness with a filesystem, shell, skills, memory, Browser, and Code Interpreter. Harness agents can switch model providers mid-session. Pyrana's Harness supports native tool calling, planning, subagents, checkpoints, and workflow fan-out to specialized agents per entity and group.

Pyrana assigns one model per agent and does not switch models mid-run, which keeps runs comparable. In a Pyrana workflow, each agent pulls only what its job needs through tools scoped to it, reads what siblings and prior runs published, and publishes back to the App as versioned resources. Tools hold the query; agents pass parameters such as entity and period.

Governed actions and approvals

AgentCore can deny or condition a tool call. Pyrana routes the call to people who decide, and records exactly what they approved. AgentCore Policy evaluates every Gateway request against permit and forbid rules over the principal, tool, and input parameters, including session history, such as requiring an earlier approval or capping a running total. Building the approval itself, who reviews, where, and with what evidence, is the team's work.

In Pyrana, a tool approval policy over typed arguments decides which invocations need a person. A tripped policy freezes the operation, exact arguments, scope, and evidence under a hash and queues it to a named approval lane. Reviewer eligibility is checked at decision time, the frozen invocation is revalidated before dispatch, and dispatch is idempotent. AgentCore Policy and Pyrana policies can coexist: Pyrana decides the business approval, and an AgentCore Gateway can still enforce its own rules on the downstream call.

Building the application

On AgentCore, the application around the agent is yours to build. On Pyrana, it is configuration plus a frontend. AgentCore provides an invocation endpoint, streaming, and AG-UI protocol support for agent frontends. The pages, records, review queues, versioned documents, and business rules of an application are a separate build, typically on Lambda, API Gateway, DynamoDB, and a frontend framework.

A Pyrana application declares its pages, and the platform hands the agent the exact page context a person is looking at. Outputs are immutable, attributed resource versions; publishing against a stale version is refused. People can ask the copilot for personal pages, which compile without network access or authority and stay read-only. With clean data available, an application typically takes about a week to stand up.

Governance and security

AgentCore secures agents as AWS resources; Pyrana authorizes every call as a business operation. AgentCore Identity federates with Cognito, Okta, Entra ID, and Auth0, supports On-Behalf-Of token exchange, and stores credentials in AWS Secrets Manager. Policy decisions are logged to CloudWatch. VPC, PrivateLink, and resource-based policies cover the network. Pyrana authorizes in layers: tenant, App membership, access profile, scope entitlement, and approval lane.

Pyrana's gate writes the execution row and audit record in one transaction before dispatch, and fails closed, so unauthorized things read as absent. Reading a record and approving a change are separate permissions. The user's principal passes through to Databricks and Snowflake row-level security. Pyrana is SOC 2 aligned and supports customer programs under HIPAA, SOX, ISO 27001, and PCI DSS.

Operations

AgentCore operates agents across AWS regions; Pyrana operates applications with a release lifecycle. AgentCore Runtime runs in 21 commercial regions plus AWS GovCloud (US-West), with narrower coverage for some services: the Harness in 16 regions and AWS Agent Registry in 5. Observability uses OpenTelemetry and CloudWatch, and Harness versions are immutable with named endpoints for rollback.

Pyrana's lifecycle covers the whole application: push compiles the App configuration into an immutable version, activate moves the active pointer under audit and requires an App owner, rollback activates a prior version, and deploy ships a frontend image. Workflows run on Temporal workers, so a run waiting for approval survives restarts and deploys. Pyrana runs on Azure, as SaaS on a dedicated private tenant or in the client's own infrastructure for large enterprises.

Cost structure

AgentCore is per-service consumption; Pyrana is a platform subscription plus implementation. AgentCore lists Runtime at $0.0895 per vCPU-hour and $0.00945 per GB-hour for microVMs, Gateway at $0.005 per 1,000 invocations, Policy at $0.000025 per authorization request, and separate meters for Memory, Identity, Evaluations, and Registry. Observability is billed through CloudWatch. The Harness has no separate charge.

Pyrana's cost is an enterprise platform subscription and implementation, and model usage runs on the client's own keys. Small, medium, and large routing for platform jobs keeps cost in proportion to the task. A first engagement, including SSO, access profiles, the approval policy, and loading the policy library into cortIQ, runs about six weeks.

What it takes to ship the same application

The reference application: a person or agent drafts a purchase request; amounts above a threshold need a finance approver; the request waits durably for the decision; everything is recorded.

Using them together

• AgentCore tools in Pyrana. AgentCore Gateway exposes APIs, Lambda functions, and Managed Knowledge Base as MCP tools. Pyrana supports MCP servers and gateways as tool sources, so a Pyrana agent can call them, with Pyrana's gate and approval policies applied first.
• Pyrana in AgentCore agents. Each Pyrana App exposes an MCP server. An AgentCore agent can call it directly or through a Gateway HTTP passthrough target, which adds AgentCore Policy and observability on the AWS side while Pyrana authorizes the call as the user.
• Data on AWS. Pyrana's REST, ODBC, Databricks, and Snowflake tool sources reach the data platforms an enterprise already runs, with the user principal passed through to Databricks and Snowflake row-level security.
• Models. Pyrana assigns models per agent through adapters for providers such as Anthropic and OpenAI, with the client's own keys.

When not to choose Pyrana

• Every component must run inside your own AWS accounts. Pyrana runs on Azure.
• You are building an internal agent platform for developers, with approved tools and shared memory, and no business application on top. AgentCore is designed for that.
• You need agent infrastructure in AWS GovCloud (US-West).
• The work is a single agent, such as a coding or research agent, where a filesystem, shell, and sandbox matter more than pages, approvals, and versioned outputs.
• You want to add policy and evaluation in front of agents already running on Lambda, EKS, or elsewhere, without changing how they are built.