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Cloud Services/Agentic Solutions

01CLOUD SERVICES · AGENTIC SOLUTIONS FOR LINES OF BUSINESS

The agents we built for cloud teams — now for yours.

Meridian proved the pattern: an agent that retrieves live data, correlates it, and answers with evidence — in production, inside the customer’s boundary. The same discipline now ships custom agents for finance, operations, customer support, and supply chain — on Amazon Bedrock and AgentCore, integrated into the ERP, ITSM, data, and ticketing systems your teams already run.

FINANCE / OPERATIONS / SUPPORT / SUPPLY CHAINDiscovery to production in weeks

Built on Amazon Bedrock & AgentCore — integrated into the systems your teams already run

Amazon BedrockBedrock AgentCoreERP integrationsITSM integrationsData platformsTicketing systemsEvaluation suitesGuardrailsAudit trailsRollback paths

02WHERE AGENTS EARN THEIR KEEP

Four practices. One production discipline.

The best agent use cases share a shape: a team spending its day retrieving, correlating, and acting on data spread across systems that don’t talk to each other. That is exactly the work agents do well — when they are engineered like production software.

Finance · Line-of-Business Agents

The controller’s question, answered with the ledger attached.

Close-cycle reconciliation support, spend and variance analysis, policy checks on transactions — agents that pull from the ERP and answer the controller’s question with the ledger evidence attached.

ERPAmazon BedrockAgentCoreLedger evidence
Bring us a finance use case →

Operations · Line-of-Business Agents

Status that assembles itself.

Agents that correlate ITSM records, operational data, and runbooks — so the answer to “what’s blocking this?” takes seconds, with the trail to prove it.

ITSMOperational dataRunbooksEvidence trail
Bring us an operations use case →

Customer Support · Line-of-Business Agents

Agents that resolve with context.

Agents that pull entitlement, history, and product data from the systems of record before drafting the response — and escalate with a complete case file when a human should decide.

Ticketing systemsSystems of recordEntitlementCase history
Bring us a support use case →

Supply Chain · Line-of-Business Agents

Exception handling at machine speed.

Agents that watch orders, inventory, and logistics signals across systems, surface the exceptions that matter, and prepare the corrective action for approval.

OrdersInventoryLogistics signalsApproval workflow
Bring us a supply chain use case →

03ENGINEERED IN FROM DAY ONE

Safety is engineered in. Never bolted on.

Evaluation suites define what good looks like before the agent ships — and measure it against the workflow’s real cases before and after every change. Guardrails constrain tools and actions to the scoped workflow: the agent can do its job and nothing else. Every retrieval, reasoning step, and action lands in a trail your auditors can walk, and every action has a reverse gear. The same discipline runs our own platforms in production.

AGENT RUN · SCOPED WORKFLOWIN YOUR BOUNDARY
erp.queryledger data retrieved from the system of record
guardrail.checktool call constrained to the scoped workflow
eval.suiteoutput measured against the workflow’s real cases
audit.trailevery retrieval, step, and action logged
rollback.pathreverse gear prepared before the action runs
aws.boundaryprompts, data, and outputs stay in your account
Weeks
Discovery to production
4
LOB practices
100%
Inside your AWS boundary
0
Shipped without safeguards
ILLUSTRATIVE RUN · STRUCTURE IS REAL, ROW VALUES ARE ILLUSTRATIVE

04THE GOVERNANCE FRAME

Business agents answer the same four questions.

Before a line-of-business agent acts — in the ERP, the ticketing queue, the supply chain — the action is bound into an execution contract. If any answer is missing, the action does not run.

EXECUTION CONTRACT #LB-00417 DECISION: ALLOWED

01 INTENT

What is the agent attempting — and for which workflow?

Every action is bound to the business workflow scoped in discovery, with an objective the workflow’s owner can read in plain language. No articulable intent, no execution.

02 SCOPE

Exactly which business systems may be touched?

The ERP, ITSM, data, and ticketing integrations are enumerated before execution. Guardrails constrain tools and actions to the scoped workflow — the agent can do its job and nothing else.

03 IMPACT

What happens if it succeeds — or fails?

Every action the agent can take has a reverse gear — reversibility is a design requirement, not an afterthought. Actions that need judgment escalate to the workflow’s owner.

04 EVIDENCE

What justifies the decision?

Every retrieval, reasoning step, and action is written to a trail your auditors can walk — and agent quality is measured by evaluation suites before and after every change.

EVALUATIONPASSED SCOPESCOPED WORKFLOW IMPACTREVERSIBLE AUDITLOGGED DECISIONALLOWED

Contract identifier and status metadata shown are illustrative. Agents are deployed on Amazon Bedrock inside your AWS account — prompts, retrieved data, and outputs never leave the environment you govern.

05HOW IT SHIPS

Discovery to production in weeks — because the hard parts already exist.

Most enterprise GenAI programs stall between the demo and the deployment. Ours don’t, because we are not inventing the architecture per engagement — we are applying patterns that already run our own platforms in production.

01

Use-case discovery

A working session with the line-of-business team to find the workflow where an agent pays for itself — scored for data availability, action safety, and measurable outcome before anything is built.

02

Build & integrate

The agent is engineered on Amazon Bedrock and AgentCore inside your AWS account, with tool integrations into your ERP, ITSM, data, and ticketing stack — scoped to the workflow, nothing more.

03

Evaluate & ship

Evaluation suites define what good looks like before go-live; guardrails, audit, and rollback are load-tested with the workflow’s owners. Production means measured, not hoped.

06QUESTIONS, ANSWERED PLAINLY

What business and IT leaders ask together.

Which lines of business do you build agents for?
Finance, operations, customer support, and supply chain are the core practices — anywhere a team spends its day retrieving, correlating, and acting on data spread across enterprise systems. Each agent is scoped to your actual workflows, built on Amazon Bedrock and AgentCore, and integrated into the ERP, ITSM, data, and ticketing systems the team already uses.
How long until an agent is in production?
Weeks, not quarters. Engagements run from use-case discovery to a production agent in weeks, because the platform layer — Amazon Bedrock, AgentCore, and our production-hardened patterns for evaluation, guardrails, audit, and rollback — already exists. The work is scoping the use case and engineering the integrations, not inventing the architecture.
Where does the agent run — and where does our data go?
Inside your own AWS boundary. Agents are deployed on Amazon Bedrock within your account, so prompts, retrieved data, and outputs stay in the environment you already govern. There is no CAELION-hosted inference service and no data egress.
How do you make agents safe enough for production?
Safety is engineered in from day one, not appended before go-live: evaluation suites that define what good looks like before the agent ships, guardrails that constrain tools and actions to the scoped workflow, a full audit trail on every step, and rollback paths for every action the agent can take. It is the same discipline that runs our own platforms in production.

07RELATED SERVICES

The same discipline, elsewhere in the practice.

PLATFORM

Agentic Cloud Operations (Meridian)

The agent pattern in production for cloud teams: plain-English questions, evidence-backed answers in ~5 seconds, read-only by default.

Cloud Services →

EXPERTISE

AWS Professional Services & Expert Hub

Data, analytics, and GenAI enablement on native AWS services — the foundations line-of-business agents are built on.

Cloud Services →

OPERATIONS

Managed Cloud Operations (PODs)

Human-plus-agent operations 24×7 — the model your line-of-business agents inherit once they’re live.

Cloud Services →

Bring the workflow that eats your team’s week.

In a use-case discovery session, we’ll score it for agent fit — data availability, action safety, measurable outcome — and show you what the production path looks like, in weeks.

Built on Amazon Bedrock & AgentCore · Deployed inside your boundary · Evaluation, guardrails, audit & rollback by design