Cloud and infrastructure
Amazon Web Services
Chosen for the workload.
Design and integrate applications, data and AI workloads on AWS when its services, operating model and regional options fit your business requirements.
- API / events
- Compute
- Data stores
- Bedrock
- Operations
- Human review
Layered AWS architecture from API and compute through data stores to Bedrock assistance and operations.
AWS becomes useful when a collection of services supports an accountable business process. Emerge designs applications, document workflows and data exchange around the transaction that must complete, the people who can approve it, and the evidence an operator needs when something fails. We work with existing accounts and enterprise systems, so a cloud programme can improve one workflow without requiring an estate-wide replacement.
The starting decision is workload fit. A document queue, a customer API and a long-running container have different execution, storage and recovery requirements. We compare AWS with Azure, Google Cloud and Cloudflare using data location, service availability, integration dependencies, operating skills and whole-life cost. Where Emerge supplies service consumption, the billing model connects measured usage to an agreed workload or customer rather than hiding it inside an unexplained infrastructure total.
Choose the right starting point
Product expertise, in detail.
Amazon Bedrock
Design bounded AI tasks around approved knowledge, selected models, review requirements and a task-level evaluation set. Model access and regional availability are confirmed for the account before a pilot is scoped.
Document processing with Textract
Turn document intake into extraction, correction and approval. Preserve the relationship between original pages, extracted fields and reviewer decisions so a downstream system receives traceable information.
Lambda, Step Functions and SQS
Connect systems using explicit event contracts, queue boundaries and recoverable orchestration. A successful receipt, a completed transformation and an accepted business update are tracked as different states.
ECS, Fargate and EKS
Select container delivery around deployment complexity, runtime dependencies and the team that will operate it. Kubernetes is assessed where its control is useful; it is not an automatic prerequisite.
S3 and application data stores
Define object retention, relational requirements and access patterns before choosing storage. Separate incoming evidence from validated records and the read models used by applications.
Cloud operations and consumption
Bring release identity, monitoring, recovery exercises and cost allocation into the delivery scope. Operating records explain which application consumed a service and who owns unusual demand.
The starting point
What needs to change.
Incoming documents and records arrive in different formats, while downstream teams need an approved, consistent representation.
Background processing can acknowledge receipt long before a business update completes, leaving operators without a reliable completion signal.
Cloud bills group services differently from the customers, products and teams that actually create demand.
What we deliver
From opportunity to working systems.
Reviewed document automation
Connect extraction and AI assistance to a reviewer workflow, with explicit rejection, correction and acceptance states.
Reliable application integration
Build event-driven interfaces that survive duplicate delivery, partial destination outages and schema changes without silently losing work.
Transparent cloud consumption
Allocate service usage to operational owners and expose the assumptions behind customer billing, internal chargeback and capacity decisions.
Illustrative solution architecture
How the pieces work together.
Bring context into the workflow, connect the right solutions, and make progress visible.
01 Understand the context
Signals & knowledge
Use the context and information already in place.
- Business priorities
- Trusted knowledge
- Operational data
02 Connect the solutions
Reviewed document automation
Reliable application integration
Transparent cloud consumption
03 Put it to work
Teams & operations
Connect people and systems to the next useful action.
Measured outcomes
Track agreed measures, learn, and improve the workflow.
Built around your existing technology
Implementation design
How the pieces work together.
Document to reviewed record
An illustrative intake flow places the original document in controlled object storage, queues extraction, and returns fields alongside their source locations for human review. Approved records enter the business system through a versioned interface. Retries cannot create a second accepted record, and rejected material remains available to an authorised reviewer under an agreed retention rule.
Receiving gateway to business API
Validate incoming messages against a source contract before transformation. Queue downstream work when a destination is unavailable, attach a correlation identifier across processing stages, and reconcile accepted records against the receiving application. The interface can connect an AWS component to an existing ERP or another cloud without moving the authoritative system.
Decisions to make early
Identity and deployment boundaries
Separate application roles from deployment roles, restrict access to the exact resources required, and prefer short-lived deployment credentials where supported. Test a denied operation as deliberately as a successful request. Document who can change an integration contract or replay a failed batch.
Consumption and recoverability
Meter requests, processing activity and storage against business volumes, then reconcile those measures with provider billing. Budgets are decision thresholds, not proof that a service will stop spending. Recovery requirements include restoration of data and resumption of in-flight work, with responsibilities agreed before release.
Our approach
A clear path into delivery.
Start with the business problem. Make each stage useful, reviewable and owned.
- 01
Inspect sample documents, API payloads and account boundaries; agree the authoritative record and success criteria for one complete workflow.
- 02
Implement the selected AWS components with repeatable deployment, failure queues, representative performance checks and measured consumption.
- 03
Rehearse replay and restoration with the operating team, then hand over access ownership, release controls and a reconciliation runbook.
Go deeper
Build a more informed brief.
Explore product-specific implementation, architecture and operating guidance for Amazon Web Services.
Amazon Bedrock implementation for governed AI workflows
Connect Bedrock models to approved knowledge and business tools, with task evaluation, human review and accountable usage.
Read the guide Amazon ECS, AWS Fargate and Amazon EKSAWS container platforms for enterprise applications
Choose ECS, Fargate or EKS around application needs, with secure delivery pipelines, health checks and practical operational ownership.
Read the guide AWS operations and cost managementAWS cloud operations, resilience and usage management
Operate AWS applications with accountable identity, release controls, observability, tested recovery and transparent consumption allocation.
Read the guide Amazon S3, DynamoDB and Amazon RDSAWS data platforms and governed data receipt
Design reliable data intake, storage and access across S3 and application databases, with validation, retention and downstream ownership.
Read the guide Amazon Textract and Amazon BedrockIntelligent document processing on AWS
Turn document intake into structured, reviewable records using Textract, approved context and a traceable human review workflow.
Read the guide AWS Lambda, Step Functions and Amazon SQSAWS serverless integration and event-driven workflows
Build reliable handovers with Lambda, Step Functions and SQS, including duplicate protection, reconciliation and operational visibility.
Read the guideRelated Agentforce integration guides for Amazon Web Services.
These integration guides examine specific systems, access boundaries and illustrative use cases.
Practical questions
Before we begin.
Can AWS coexist with our other clouds?
Yes. We identify the system of record and place interfaces at clear boundaries. Cross-cloud transfer, identity, support ownership and latency are costed and tested explicitly. We retain an existing platform when moving it would add risk without improving the workflow.
How does an AWS engagement start?
Bring one transaction or document process, its current failure points and the available source data. The first increment produces an architecture decision, representative working path, reconciliation checks and a usage baseline that supports an informed expansion decision.
Explore the detail
Related work and resources.
See the approach in context. Client engagement stories are anonymised; related examples may come from other sectors or platforms.
Connected expertise
Capabilities
Technologies
Solutions
Your next move
Bring us the business problem.
Pick a time below. We will help you define a useful starting point, the expertise you need and a practical path to delivery.
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