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Building on Amazon Bedrock AgentCore yourself, or working with Agentifiers

Amazon Bedrock AgentCore is a set of AWS-managed services for building, deploying, and operating AI agents, including runtime, memory, gateway, identity, policy, observability, and evaluations. Your team assembles them into its own agents and product layer. Agentifiers brings a finished multi-tenant agent platform, plus a team that builds agents with you, in your AWS account.

AgentCore details checked against AWS documentation onOctober 19, 2026. AWS updates AgentCore often, so follow the linked sources for current details.

Amazon Bedrock AgentCore

What AgentCore gives you

AWS describes AgentCore as an agentic platform for building, deploying, and operating agents securely at scale, with any framework and any foundation model, and without infrastructure management. Its services can be used together or independently (AWS overview):

Runtime. Serverless hosting for agents and tools, with each user session in a dedicated microVM. Sessions run up to 8 hours on microVMs, or up to 14 days on Instances.
Memory. Short-term memory for multi-turn conversations, and long-term memory that persists across sessions.
Gateway. Turns APIs, Lambda functions, and existing services into MCP-compatible tools, and connects to existing MCP servers.
Identity. Agent identity, access, and authentication that works with existing identity providers such as Amazon Cognito, Okta, and Microsoft Entra ID.
Policy. Deterministic rules, written in Cedar or in natural language, that are evaluated against every tool call through Gateway before it runs.
Observability. Traces, debugging, and monitoring of each step an agent takes, with OpenTelemetry-compatible telemetry.
Evaluations. Automated assessment of how well agents and tools perform, before and after deployment.

AgentCore also includes a managed agent loop (Harness), a code interpreter, a browser tool, a registry, and services for optimization and payments (overview). Each Runtime update creates an immutable version, and endpoints can point to specific versions for environments such as development and production (versioning). Pricing is consumption based, with no upfront commitments or minimum fees (pricing).

AWS lists agent platforms as one of the things you can build with AgentCore: a paved path for your developers or customers, with approved tools, shared memory stores, and governed access (overview).

Your part

What your team still designs and builds

AgentCore provides building blocks. Turning them into agents that do real work for your business is your team’s job:

The agents. Which framework, which model, what each agent does, and how its prompts, tools, and evaluation sets are maintained.
The workflow. Mapping the work with the people who do it, and deciding where approval points belong. AgentCore Policy can require, for example, that an approval was granted before a transfer (Policy). Who approves, where the request reaches them, and what they see are design decisions you make.
The tenant model, if you serve many customers. AWS’s own guidance on multi-tenant agents covers onboarding, tenant isolation, and noisy-neighbor policies, and notes that you may need to introduce constructs that enforce each agent’s isolation requirements (tenant isolation).
The release process. How each version is evaluated, promoted between environments and accounts, and rolled back.
The product layer. How your people or customers reach agents, whose brand they see, how usage is attributed to each tenant for billing, which retention and export policies apply, and the infrastructure as code that ties it together.

For many teams, that is the right amount of control. If you have platform engineers, a clear product, and want every layer in your own hands, building on AgentCore directly is a sound choice.

Agentifiers

What Agentifiers brings

Agentifiers is a team with a platform: Deployments.ai, a source-available, multi-tenant agent platform. The source release is coming soon, under FSL-1.1-ALv2. Deployments.ai runs in an AWS account in your AWS Organization (BYOC), or hosted and managed by us in our AWS account. It includes:

A multi-tenant model. Organizations, projects, and environments isolate each tenant’s agents, data, and credentials, whether tenants are your departments or your customers.
Agents as code. Agents, tools, and policies ship as immutable, versioned releases, with canary rollout, promotion from dev to prod, and rollback.
Human approvals. Any tool call can be marked approval-required. The run pauses, asks the right person, and resumes on their answer.
Durable workflows and memory. Long-running, resumable runs with schedules, so work survives restarts and can wait on people.
Traces and evaluations. Every run is traced step by step, and evaluation suites gate each release before it reaches production.
Governance and metering. Retention policies, tenant export, erasure, signed audit-log exports, and usage metering for each tenant.
Channels. Slack, email from your domain, Telegram, RCS business messaging, or inside your product through the API, SDK, and CLI.
White-label. Your name, your domain, and agent identities your people recognize.

For internal agents, we also do the work: we map the workflow with your team, build and evaluate the agents, and operate them until you take over. Foragents in your product, your engineers build on the platform, self-hosted (coming soon), set up by us in your AWS account, or hosted. See the platform for the details.

Side by side

AgentCore and Agentifiers, compared

AgentCore column based on AWS documentation checked October 19, 2026.
Comparison	Building on AgentCore yourself	Working with Agentifiers
What you start with	AWS-managed services you compose: runtime, memory, gateway, identity, policy, observability, evaluations, and more	A finished multi-tenant agent platform, set up for you
Where it runs	AWS-managed services, used from your AWS account	A dedicated AWS account in your AWS Organization, or hosted Deployments.ai in our AWS account
Frameworks and models	Any framework and any foundation model, your choice	Agents defined as code on the platform; models only through providers you approve, on your own keys
Tenant model	Yours to design, with AWS multi-tenant guidance	Organizations, projects, and environments isolate each tenant’s agents, data, and credentials
Releases	Immutable Runtime versions, with endpoints you point at them; the promotion process is yours	Versioned releases with canary rollout, evaluation gates, promotion from dev to prod, and rollback
Human approvals	Policy can require conditions such as a prior approval; how people approve is yours to design	Approval-required tool calls: the run pauses, asks the right person in Slack or email, and resumes
Where people meet agents	Your choice of front end and integrations	Slack, email from your domain, Telegram, RCS business messaging, or your own product through the API
Who does the work	Your engineers	Our team with yours for internal agents; your engineers on the platform for agents in your product
How you pay	Consumption-based AWS pricing, plus your team’s time	Our fees by invoice; in BYOC, AWS bills the infrastructure on your account

When AgentCore fits

When building on AgentCore yourself is the right call

You have platform engineers with time, and agents are core to what you build.
You want to choose every layer yourself: framework, models, tenancy, and front end.
Your engineers already know the workflows, so you don’t need a team to redesign them with your people.
You want AWS to run the agent infrastructure as managed services.

That describes many teams, and AgentCore gives them a strong foundation.

When Agentifiers fits

When working with Agentifiers fits better

You want AI agents doing real work in your AWS account without building an agent platform first.
You need the product layer now: tenants, approvals, releases, channels, per-tenant metering, and white-label.
You want a team to map and redesign the workflow with your people, not just infrastructure.
You want a platform you can keep: the agents are code in your repository, and the platform source is coming soon under a source-available license.

Weighing more than these two routes? See five ways to get AI agents into production, or go back to all comparisons. For how we price engagements, seepricing.

AgentCore questions

If you have platform engineers with time, want to choose every layer yourselves, and your engineers already know the workflows, building on AgentCore directly is a sound choice. If you want governed agents doing real work in your AWS account without building the product layer first, that is what Agentifiers provides.

No. The platform is built on standard AWS services such as Lambda, ECS on Fargate, DynamoDB, S3, KMS, EventBridge, and SQS, and is provisioned with OpenTofu in a dedicated AWS account in your AWS Organization. See BYOC for AI agents.

AgentCore is a set of AWS-managed services that your team uses from its own AWS account, with consumption-based pricing. Deployments.ai, the platform Agentifiers sets up, runs in a dedicated AWS account in your AWS Organization, or hosted and managed by us in our AWS account.

Sources

AWS documentation, checked October 19, 2026.

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