Move from AI experiments to an enterprise agent mesh.
Glacien's Enterprise Agentic Mesh on AWS gives enterprises the governed foundation to design, deploy, and scale AI agents across every business function — built natively on Amazon Bedrock AgentCore, delivered in weeks, yours to extend for the next decade.
The problem every enterprise is hitting right now.
Your teams are already building agents — in silos.
Support bots here, document reviewers there, procurement automations somewhere else. No one knows what exists.
Agent sprawl is the new shadow IT.
Duplication piles up, governance fragments, compliance exposure grows, reuse approaches zero.
The market has decided.
Gartner projects 40% of enterprise applications will embed AI agents by end of 2026. 40% of agent projects will be cancelled by 2027 — not because of the models, but because of missing platforms underneath.
The question is no longer whether to build agents. It is whether you are building them on a platform that can scale, govern, and survive the next five years.
One platform. Eight capabilities.
Yours to extend forever.
A single governed platform on AWS that lets your enterprise design, deploy, operate, and evolve AI agents — across every business function — on one foundation.
1 architecture
∞ agents
Agent framework
Build in the framework your team chose. The mesh does not force one SDK.
Production runtime
AgentCore Runtime — dedicated isolation, 8-hour sessions, autoscaling. No infrastructure to manage.
Orchestration
Supervisor + specialist inside one solution. A2A protocol across teams and clouds.
Connectors
AgentCore Gateway. Every API, Lambda, and SaaS system becomes a governed MCP tool.
Knowledge & memory
Bedrock Knowledge Bases for enterprise retrieval. AgentCore Memory for stateful, personalised execution.
Registry
AWS Agent Registry — one governed catalog for every agent, tool, skill, and MCP server.
Governance
Bedrock Guardrails for safety. AgentCore Policy for tool control. AgentCore Identity for authentication.
AgentOps
AgentCore Observability and Evaluations — full traces, quality scoring, cost, drift detection.
What enterprises see in the first three months.
Six outcomes, consistent across deployed references.
Three steps. Every use case.
Repeatable across procurement, claim triage, contract review, customer escalation, and every workflow after.
You describe a business outcome
A procurement decision. A claim triage. A contract review. A customer escalation. The enterprise goal becomes the entry point — not an IT project.
The mesh routes, reasons, acts
An Orchestrator receives the request and delegates to specialists — some internal, some cross-team via A2A. Each uses MCP-governed tools. Every step is policy-checked, identity-scoped, and observable.
You get a defensible answer — or an approved action
Chart, narrative, number, document, ticket, email — whichever fits. Every fact is citeable. Every action previews before it fires. Every decision is auditable end-to-end.
Three starting shapes. One foundation.
The mesh is designed for your ambition, not ours. Every path starts with the same foundation. Every new agent you add later deploys onto the mesh you already own.
Lighthouse
- One high-value domain chosen with your exec team
- Full mesh primitives deployed — Runtime, Gateway, Registry, Governance
- Proves the platform pays for itself in year one
Portfolio of five
- Five agents across adjacent business functions
- Shared connectors, shared registry, shared governance
- Reuse patterns appear from the first sprint
Broad initial rollout
- Ten agents seeded across multiple BUs
- Mesh fully populated with skills and connectors on Day 1
- Full enterprise mesh from the outset
Every path starts with the same foundation. Every new agent you add later deploys onto the mesh you already own.
The mesh in your enterprise, across every domain.
A governed mesh supports every major enterprise function. Every agent plugs into the same mesh. Every agent benefits from shared tools, shared governance, shared observability.
- Invoice reconciliation
- Expense audit
- Month-end close assistant
- Vendor evaluation
- Contract review
- Spend analysis
- Contract redline
- Regulatory monitoring
- Dispute triage
- Onboarding
- Policy Q&A
- Employee case routing
- Incident triage
- SRE investigation
- Change management
- Policy check
- Control testing
- Audit trail assembly
- Account research
- Proposal drafting
- Renewal analysis
- Conversational data access
- Decision support
- Reporting
- Demand sensing
- Vendor coordination
- Exception handling
Every layer built on the newest AWS agentic services.
No LangChain-on-EC2 pretending to be a platform. Your data stays in your AWS account — Bedrock traffic over VPC endpoints, customer-managed KMS keys.
| AWS service | Role in the mesh |
|---|---|
| Amazon Bedrock AgentCore Runtime | Supervisor + specialist orchestration, microVM isolation, A2A native. |
| Amazon Bedrock AgentCore Gateway | MCP tool layer — OpenAPI, Smithy, Lambda, API Gateway, MCP server targets. |
| AWS Agent Registry GA Apr 2026 | Governed catalog for agents, tools, skills, and MCP servers. |
| Amazon Bedrock AgentCore Memory | Short-term session context + long-term cross-session memory. |
| Amazon Bedrock Knowledge Bases | Enterprise RAG across S3, SharePoint, Salesforce, Confluence, Aurora. |
| Amazon Bedrock Guardrails | PII redaction, denied topics, toxicity, prompt injection, Automated Reasoning. |
| Amazon Bedrock AgentCore Policy | Deterministic tool-use control with Cedar grammar or natural language. |
| Amazon Bedrock AgentCore Identity | Inbound, outbound, on-behalf-of authentication with managed OAuth providers. |
| Amazon Bedrock AgentCore Observability | OpenTelemetry-native traces, sessions, spans, metrics. |
| Amazon Bedrock AgentCore Evaluations | Automated quality scoring — correctness, helpfulness, safety, goal success. |
| Amazon Bedrock models | Claude Sonnet, Haiku, Nova, Titan, fine-tuned — the right model for each task. |
| AWS Lake Formation | Row-level security for data-facing agents. |
| AWS KMS · CloudTrail · VPC endpoints | Customer-managed encryption, full audit trail, private networking. |
| AWS CDK | Reproducible infrastructure-as-code deployment. |
We build agentic AI that runs in production.
Glacien designs and deploys multi-agent systems on your platform, customised to your operations — taking enterprise AI from proof-of-concept to production in weeks, not months.
Banks, insurers, maritime operators, and engineering firms trust us with the workflows where the cost of manual work is measured in millions and the margin for error is zero. AWS Select Partner with agentic AI specialisation. We do not advise. We build, deploy, and stand behind what we deliver.
Agentic AI, engineered.
Ready to stop building agents in silos
and start running a mesh?
Book a 30-minute platform walkthrough with our solutions team. We will show you the reference mesh, the lighthouse use case running live, and scope a platform foundation tailored to your business priorities. No slides that waste your time.