QUICK VERDICT
The Answer in Brief
Amazon Bedrock AgentCore is the better choice when your workloads, data and security tooling already run on AWS, your engineers want framework freedom (LangGraph, CrewAI, Strands Agents, Google ADK or their own), and pay-per-second infrastructure that scales to zero fits how you budget. AWS handles the isolation, scaling and telemetry plumbing.
VDF AI is the better choice when agents have to run in your own datacenter or an air-gapped enclave, when business teams need a governed visual builder rather than a set of primitives, or when you want a fixed annual platform cost with unlimited users instead of a dozen usage meters. For the wider field, see our 2026 vendor landscape.
PRICING & HOSTING
AgentCore Pricing Meters and Hosting Model
One vendor bills each service by use; the other sells a year of capacity.
Amazon Bedrock AgentCore
Billing model checked September 2026 on the AgentCore pricing page
No upfront commitment or minimum fee; AWS says a discounted committed baseline for microVMs arrives by October 2026. Model inference, ECR or S3 storage for agent code, and network transfer are billed on their own AWS price lists.
VDF AI Pricing
Mechanics as listed on our pricing page
Usage inside the permitted surplus above your allowance is not charged, and part of any unused capacity carries into the next term at renewal.
Primitives versus a finished platform
AgentCore’s strength is that every piece is optional. You can adopt Runtime alone, add Gateway later and switch frameworks without touching infrastructure. The flip side is assembly: approval flows, a builder for non-developers, an evidence model for auditors and a spend forecast all have to be designed by your team on top of those services. VDF AI arrives with those layers built, and it installs just as well in an AWS account as in your own datacenter or a sealed network. Our on-premises page walks through the install.
GOVERNANCE
Identity, Policy & Audit
AWS enforces its controls at the Gateway; VDF AI enforces them in a runtime you host.
Agent identity
Tool-call policy
Guardrails
Tracing and telemetry
Data residency
Audit evidence
BUILD MODEL
Assembling Agents: Kit or Platform
AgentCore supplies services to compose; VDF AI supplies a governed workspace.
AgentCore Building Blocks
- Runtime — microVM sessions of up to 8 hours, or EC2 Instances for sessions of up to 14 days
- Harness — a managed agent loop defined by model, prompt and tools in a single API call
- Gateway — turns APIs, Lambda functions and existing MCP servers into tools, with one-click Salesforce, Slack, Jira, Asana and Zendesk
- Memory — short-term events and long-term records that agents can share
- Browser and Code Interpreter — isolated sandboxes for web tasks and code execution
- Evaluations and Optimization — 13 built-in evaluators plus A/B tests on live traffic
- Business-user tooling — agent logic is written by developers in the framework of their choice
- Hosting boundary — every service runs inside AWS Regions
VDF AI Components
- VDF AI Networks — a canvas for multi-agent flows with Human Approval and MCP Action nodes
- VDF AI Agents — a guided builder from basics to review, with reusable Agent Skills
- VDF AI Router — per-request model choice with budgets, rate limits and an ordered failover list
- MCP gateway — a tool server inside your perimeter, air-gapped where required
- Vault — durable run history and decision receipts
- Operations — your team or partner runs the containers; VDF AI Cloud if you prefer a hosted service
- Offline installs — images are mirrored to your registry through the documented air-gapped path
AWS-hosted agents and VDF AI can run side by side; the sequence below shows one way to split the estate.
ARCHITECTURE
What Each Stack Contains
Component lists, side by side.
Bedrock AgentCore
Modular agent services on AWS
- Harness + Runtime — the agent loop and isolated compute
- Gateway + Policy — tool access and rule enforcement
- Identity — inbound authentication and outbound credentials
- Memory — session and long-term context
- Observability + Evaluations — CloudWatch traces and quality scoring
- AWS Agent Registry — a catalogue of agents, tools and skills
The services work together or alone, with any framework and model. Running them is AWS’s job; composing them into a product is yours.
VDF AI
Integrated governed agent platform
- VDF AI Networks — multi-agent orchestration with approvals
- VDF AI Agents — builder, Agent Skills and tool registry
- VDF AI Router — SEEMR routing and air-gap mode
- MCP gateway — governed tool calls inside the perimeter
- Vault — evidence your auditors can query
- VDF AI Chat — the interface employees work in
One product from builder to audit log, packaged as containers so a single design runs on AWS, in a datacenter or offline. The platform overview describes each part.
DEPLOYMENT
Deployment & Residency Options
The physical boundary of each option, row by row. For the Google equivalent, read our Vertex AI comparison.
| Dimension | Bedrock AgentCore | VDF AI |
|---|---|---|
| Commercial cloud | 21 AWS Regions, with feature coverage varying by Region | VDF AI Cloud, or self-installed in a cloud account you own |
| US government cloud | AWS GovCloud (US-West) with Runtime, Gateway, Identity, Memory and Policy | On-prem or sovereign deployment on infrastructure you have accredited |
| Your datacenter | Managed service in AWS Regions; private systems reached through VPC and PrivateLink | Docker Compose or Kubernetes on your own servers |
| Air-gapped | No disconnected edition in the regional table | Offline install from your internal registry |
| Compute in your account | Runtime Instances run on AWS-managed EC2 in your account | Every component runs in your account or datacenter |
| Scaling | Automatic, from zero to very large session counts | Sized by you, or handled for you on VDF AI Cloud |
| Content use | AWS notes AgentCore may store content to improve the service for your own use, not other customers’ | Self-hosted; external model calls happen only where router policy allows |
Region and feature coverage from the AgentCore regional table; content-use note from the AgentCore overview. Both verified September 2026.
FAIR PLAY
When to Choose AgentCore
For AWS-first engineering organisations, AgentCore is a strong default.
AgentCore is the right call when…
- Your data, identity and security tooling are already on AWS, and CloudWatch and CloudTrail are where your SOC looks first.
- Engineers want to keep their framework, whether LangGraph, CrewAI, LlamaIndex, Strands Agents or Google ADK, and deploy it unchanged.
- Workloads are bursty, and per-second compute that stops charging CPU during I/O wait matches your budgeting.
- Agents must run in AWS GovCloud (US-West), where Runtime, Gateway, Identity and Policy are offered.
- You are on Bedrock Agents Classic and want AWS’s own migration route through the managed harness.
- Your platform team has the capacity to build the approval, interface and evidence layers itself.
Where AgentCore is genuinely strong
Runtime hosts agents from the main open-source frameworks and any model, in or outside Bedrock, with MCP and A2A support.
MicroVM sessions with hardware-enforced isolation scale from zero to hundreds of thousands of concurrent sessions, according to AWS.
Policy sits outside the agent’s execution boundary, so its rules still hold when prompts drift or the model behaves unexpectedly.
Gateway exposes S3, DynamoDB, Aurora, Redshift and Lambda as tools, and telemetry lands in the CloudWatch account you already watch.
DECISION SIGNALS
When VDF AI Is the Stronger Choice
Situations where a managed AWS service stops being the easy answer.
Agents must run outside AWS
A regulator, a customer contract or a classified network rules out a hyperscaler region. VDF AI installs in your datacenter or a sealed enclave, with the audit Vault alongside.
You want a platform, not a kit
Building approvals, a business-user builder, evidence exports and cost controls on top of AgentCore is a real project. VDF AI ships them, so the platform team configures rather than constructs.
One budget line for the year
Per-second compute, per-request gateway and policy meters, memory records and CloudWatch ingestion produce a bill that shifts with every design change. Capacity Licensing fixes the platform cost up front.
Split traffic between cloud and local models
When some prompts may reach an external model and others must stay on a local Llama or Mistral deployment, the VDF AI Router enforces that split per request and records why.
An exit plan is required
If the board wants agents that could move between AWS, another cloud and on-premises, container delivery keeps that door open. Identity, memory and policy built on AgentCore services would need rebuilding elsewhere.
Auditors ask for receipts
Receipts that tie prompt, sources, model, tools and outcome together sit in a Vault you host, ready for an EU AI Act or sector review without an export from CloudWatch.
MIGRATION
Moving Workloads Step by Step
Whether you are leaving Bedrock Agents Classic or narrowing AgentCore’s scope, this order keeps risk low.
Inventory by boundary
List every agent with its data classes, tools and action groups. Agents whose data may stay in AWS can move to AgentCore’s harness; those destined for your datacenter or an enclave go to VDF AI.
Recreate tools as governed MCP actions
AWS’s own migration guide exposes Classic action groups as MCP tools. In VDF AI the same capabilities become MCP Action nodes with per-role grants, registered once in the tool registry.
Set model policy centrally
Decide which model families each workload may use, then encode that in the VDF AI Router: local models for restricted data, approved external providers elsewhere, each with a budget and a failover order.
Run in parallel, then cut over
Run the rebuilt network beside the AWS version on the same inputs, compare outcomes and approval traces in the Vault, and switch traffic once reviewers have signed off.
FULL COMPARISON
Capability Matrix
AgentCore capabilities checked in September 2026 against docs.aws.amazon.com and aws.amazon.com.
| Capability | VDF AI | Bedrock AgentCore |
|---|---|---|
| Product scope | Governed agent platform from builder to audit log | Modular managed services for agent infrastructure |
| Pricing | Per user on Cloud; on-prem, an annual capacity pool with unlimited users | Consumption-based per service, no minimum fee |
| Deployment | VDF AI Cloud, private cloud, on-prem, sovereign cloud or air-gapped | AWS Regions and AWS GovCloud (US-West) |
| Framework support | VDF AI Networks and Agents, with REST APIs | LangGraph, CrewAI, LlamaIndex, Strands, Google ADK, OpenAI Agents SDK or custom |
| Model choice | OpenAI, Anthropic, Gemini and Mistral models, Llama, or your own local models | Any model, in or outside Bedrock |
| Model routing and spend limits | SEEMR routing on quality, cost, latency, energy and policy, with budgets and failover | Per-user limits on requests, tokens and connection time at the Gateway |
| Visual builder | Networks canvas and a five-step agent builder | Harness configuration; logic coded in your framework |
| Tool governance | Per-role MCP grants and approval gates | Policy at the Gateway (Cedar-compatible) with Guardrails integration |
| Identity and access | Per-role tool grants; SSO on Enterprise Cloud; Entra ID SSO on-premise | AgentCore Identity with Cognito, Entra ID, Okta and a token vault |
| Memory | Living knowledge vault fed by execution history | Short- and long-term Memory shared across agents |
| Observability | Per-agent trace, audit log, cost and energy telemetry | CloudWatch dashboards with OpenTelemetry export |
| Audit evidence | Vault decision receipts and an EU AI Act evidence pack | CloudTrail and CloudWatch logs |
| Browser and code tools | Tools run as governed MCP actions inside your perimeter | Managed Browser and Code Interpreter sandboxes |
Sources, verified September 2026: AgentCore developer guide · AgentCore FAQ · AgentCore pricing · Agents Classic maintenance notice. AWS adds features and Regions often, so confirm coverage before you commit a design.
FAQ
Frequently Asked Questions
What platform and security teams ask when they look for a Bedrock AgentCore alternative.
Related resources
For teams deciding whether agents belong in a hyperscaler region or on infrastructure they run, these pages cover self-hosting, gateways and capacity pricing in more detail.
Re-Platforming From Bedrock Agents?
Pick one agent that needs to run outside AWS or clear a stricter audit. We will map its tools, model policy and approvals onto VDF AI and estimate the capacity it would draw.