Enterprise integration
Connect agents to your applications, data stores and APIs through well-defined interfaces.
AI agents that work inside your systems, under your control.
We design, build and operate AI agents that connect to your enterprise data and applications, act within defined limits, and keep people in control where it matters.
Problems we address
Demos that cannot be trusted in production
Without clear limits, evaluation and monitoring, agent behaviour is hard to predict and harder to defend.
Agents cut off from your systems
An agent is only as useful as the systems and data it can reach safely.
Unclear ownership
Who approves actions, who monitors results and who is accountable when an agent acts?
Quality and cost that drift
Usage patterns, model changes and edge cases change results over time.
Capabilities
Controlled tool use
Give each agent only the tools it needs, with limits on what it may do and approval for high-impact actions.
Knowledge and retrieval
Ground answers and actions in your own documents and live data.
Human-in-the-loop workflows
Design the points where people review, approve or take over.
Evaluation and testing
Measure accuracy and task completion against realistic test cases before and after release.
Monitoring and operations
Trace behaviour, track cost and quality, and respond when results change.
Typical use cases
- Operational assistants that answer complex questions from live data and forecasts
- Support agents for customers and employees, grounded in your knowledge
- Back-office workflows such as reconciliation, document handling and approvals
- Analyst copilots across reporting, forecasting and investigation
How we deliver
Choose the workflow and set the limits
Agree the business outcome, what the agent may do on its own and where a person decides.
Prototype with your data
Test the idea against real data and constraints early, with the people who run the process.
Integrate and secure
Connect to your systems with scoped identities, controlled tools and logging.
Evaluate before release
Run structured tests and review failures before real users depend on it.
Deploy, monitor and improve
Release with monitoring and clear ownership, then refine from real usage.
Technical foundations on AWS
Built on AWS, using managed services where they fit and custom engineering where they do not.
- Amazon Bedrock
- Amazon Bedrock AgentCore
- Amazon Bedrock Guardrails
- AWS Lambda
- Amazon API Gateway
- AWS Step Functions
- Amazon CloudWatch
- AWS IAM
- AWS Secrets Manager
- Amazon S3
- Model choice follows the task, data sensitivity, latency and cost.
Security, governance and operations
Least-privilege identity
Agents act with their own scoped permissions, not shared administrator credentials.
Controlled tool use
Approved tools only, with policy checks and approval steps for actions that carry risk.
Human oversight
People stay in the loop for decisions that need judgement, with clear escalation paths.
Audit and observability
Traces, logs and evaluation results that show what an agent did and why.
Data protection
We design so that your data stays within your AWS environment.
Related services
- Forward Deployed EngineeringCloudStraight joins architecture and execution: our architects stay close to implementation, validate designs in your real environment and help build through to production.
- Generative AI & RAGGenerative AI applications grounded in your own knowledge with retrieval-augmented generation, evaluated, guarded and operated on AWS.
Have an AI or Cloud challenge to solve?
Let's identify the opportunity and determine the right path to a working solution.
Discuss Your Initiative