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Move AI agents from prototype to production with Amazon Bedrock AgentCore
Production agents need persistent memory, scoped permissions and a full audit trail. Amazon Bedrock AgentCore (AgentCore) provides these foundations. We design it around your AWS workloads and help you operate it.
Runtime
Serverless hosting, one isolated session per user
Memory
Short-term and long-term recall across sessions
Gateway
Your APIs and Lambda functions as MCP tools
- Strands Agents
- LangGraph
- CrewAI
- LlamaIndex
- Custom code
Identity
Acts on behalf of the signed-in user
Observability
Step-by-step traces in CloudWatch, OTel compatible
Tools
Sandboxed Code Interpreter and cloud Browser
- 500+
- Customers worldwide
- 200+
- SMEs
- 50+
- Technology partners
- 24*7
- Global delivery centre
- IN + AE
- Offices in India and Dubai
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Ready to take your agent to production?
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02 Definition
What Amazon Bedrock AgentCore is
AgentCore is a set of managed AWS services for running AI agents in production. It is not a new framework and it does not replace the one you picked. It is the plumbing around your agent: where it runs, what it remembers, which tools it can reach, who it is acting for, and what it did.
You can build that plumbing yourself. Most teams who try spend months on session handling, credential brokering and tracing before the agent does anything new. AgentCore gives you those pieces as services, and you only pay for what each one uses.
One honest caveat. AgentCore is built for developers. If you want to set up an agent through configuration inside Bedrock, Agents for Amazon Bedrock may be a better fit, and we will tell you so.
- Type
- Modular, fully managed AWS services
- Frameworks
- Strands Agents, LangGraph, CrewAI, LlamaIndex or your own code
- Models
- Amazon Bedrock or other providers
- Adoption
- Use one service, a few, or all of them
- Pricing
- Consumption based, no upfront commitment
- Regions
- Multiple AWS Regions, including Asia Pacific
03 Failure analysis
Prototype vs production
Every agent we have taken live has faced these requirements. The left column works for a demo. The middle column is what your users, security team and auditors will expect.
| In the notebook | What breaks in production | AgentCore piece |
|---|---|---|
| 01Runs on a laptop or in one container. | Lots of users at once, each needing their own isolated session. Some tasks run for hours. | Runtime |
| 02Forgets everything when the kernel restarts. | Customers repeat themselves every time. The agent cannot recall a preference it was told last week. | Memory |
| 03Calls APIs with a key pasted into a .env file. | Internal APIs have to be exposed as tools safely, without every team writing its own glue code. | Gateway |
| 04Acts as the developer who wrote it. | It must act as the real user, with that user's permissions, through Amazon Cognito, Okta or your enterprise identity provider. | Identity |
| 05Does whatever the prompt lets it do. | Rules like "no refunds above the approved limit" must hold every time, enforced outside the model. | Policy |
04 Components
The stack, layer by layer
Read it from the bottom up. Runtime is the foundation. Your agent sits at the top and remains yours: your framework, your prompts, your model choice.
Agent logic
Prompts, tool definitions and orchestration in the framework your team already knows.
Model
Foundation models from Amazon Bedrock or another provider.
Gateway
Turns existing APIs, Lambda functions and services into MCP-compatible tools agents can discover.
Code Interpreter
A sandbox where the agent can write and run code for calculations and analysis.
Browser
A managed, isolated cloud browser for web-based tasks.
Memory
Short-term memory for the current conversation, long-term memory for facts and preferences across sessions.
Identity
Agent and user credentials, integrated with Amazon Cognito, Okta or your enterprise identity provider.
Policy
Deterministic rules on tools and data, enforced outside the agent code.
Runtime
Serverless hosting with session isolation, fast cold starts and support for multi-hour workloads.
Architect's note. You do not need every layer on day one. Plenty of teams start with Runtime and Observability, then add Memory or Gateway when a real need shows up. Each service also works on its own, so agents hosted elsewhere can still use Gateway and Identity.
05 Engagements
Services from strategy to operations
Five engagements that form a roadmap. Most clients join at one stage rather than at the start. Timelines are typical ranges, confirmed after an initial consultation.
-
Agentic AI strategy and use case discovery
We work out where an agent will save real time or money, and where a simpler automation would do. Then we check whether your data and systems are ready for it.
- Use case discovery and prioritisation
- How much autonomy, and where a human signs off
- Framework and model selection
- Business case and success metrics
-
Custom agent development
Our engineers build single-agent and multi-agent systems in Strands Agents, LangGraph or CrewAI, on Amazon Bedrock models, deployed to AgentCore Runtime.
- Agent design, prompts and tool definitions
- Multi-agent orchestration
- Memory design for personalisation
- RAG with Amazon Bedrock Knowledge Bases
-
Prototype to production migration
Already have agents in notebooks, containers or on self-managed servers? We harden them and move them to AgentCore, without making you rewrite the agent logic.
- Agent and framework assessment
- Containerisation and Runtime deployment
- Gateway setup for your existing APIs
- Load, security and failure testing
-
Agent security, identity and policy
Our CERT-In empanelled security practice designs the identity, access and policy controls, so each agent can do its job and nothing more.
- Identity provider and OAuth integration
- Policy definitions for tools and data
- Amazon Bedrock Guardrails for content safety
- Threat modelling and agent VAPT
-
Managed AgentOps, 24*7
Once agents are live, our Global Delivery Centre watches them around the clock, checks their quality and keeps token spend in line.
- Observability dashboards and alerting
- Continuous quality evaluations
- Cost and token usage tuning
- Incident response and model updates
07 Applications
Where agents deliver value
Agents that take real actions across your systems, with a person in the loop where it matters.
Support agents that finish the job
Check the order, issue the refund, update the CRM, and hand over to a human when the case needs one.
KYC and loan processing
Gather documents, verify details across systems and prepare the file for an underwriter, with a full audit trail.
SOC triage
Investigate alerts, enrich them with threat intelligence and suggest containment steps for an analyst to approve.
08 Questions
What architects usually ask us
Not covered here? Ask us directly. We would rather answer a specific question than send a brochure.
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