AI agent development services on Amazon Bedrock and AgentCore
AI Agent Development Services
Agents that act inside your systems, with limits you set and a log you can audit.
Dedicatted designs, builds and runs AI agents that take real actions in your CRM, ERP, ticketing and data platforms, with bounded autonomy, approval gates per action and a full audit trail. Built on Amazon Bedrock by an AWS partner with the Agentic AI Specialization and the Generative AI Competency.
- 2-week audit A use-case audit with a guardrail design and an ROI model, at a fixed price
- Every action logged Inputs, decisions and outputs recorded for each step an agent takes
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AWS Premier Tier
Agentic AI Specialization and Generative AI Competency on the same partnership -
SOC 2 + ISO 27001
Agents built and run under the same controls as our own delivery
What are AI agent development services?
What are AI agent development services?
AI agent development services design, build, integrate and run software agents that use a language model to plan and take actions inside business systems. They read records, call APIs, draft and file documents, and escalate to a person when a rule says so.
What is the difference between an AI agent and a chatbot?
A chatbot answers questions in a conversation. An agent completes a task. It reads from your systems, decides within limits you set, writes back, and logs every step so the outcome can be checked.
What does an AI agent development company do?
It picks the first process worth automating, designs the agent’s tools, permissions and approval gates, builds and evaluates it on a platform such as Amazon Bedrock, integrates it with your systems and keeps it monitored in production.
When an AI agent is the right tool
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A process with rules and expensive people in the loop
Claims, reporting, intake, routing and reconciliations. Work with a definition of done that today waits on a queue of specialists.
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Systems an agent can reach
APIs, documents or databases the agent can read and write through scoped permissions, so it acts on data rather than describing it.
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A first result you can measure
One process with a cycle time, an error rate or a cost per case we can baseline now and move within eight weeks.
Our AI agent development services
Three ways to engage. The audit is priced before it starts. Build and run are quoted from what the audit finds.
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Start here
Use-case audit
For choosing the first process and proving the case
- Duration
- Two weeks
- Price
- Fixed, agreed in the first call
- You get
- An ROI model, an agent design and a guardrail plan
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Custom AI agent development
For a process that is ready to automate
- Duration
- Four to six weeks per agent
- Price
- Quoted from the audit
- You get
- An agent in your AWS account, tested and piloted
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Run and improve
For agents already in production
- Duration
- Monthly
- Price
- Per agent, shown apart from the build
- You get
- Monitoring, cost per task and a monthly review
Chatbot, copilot or AI agent
Three things people call AI that behave differently in production. The right one depends on how much you want the software to do on its own.
- Chatbot Answers questions from documents you give it
- Copilot Suggests the next step to an expert who stays in control
- AI agent built by Dedicatted Runs a bounded process end to end and escalates by rule
| Chatbot Answers questions from documents you give it | Copilot Suggests the next step to an expert who stays in control | Our focus AI agent built by Dedicatted Runs a bounded process end to end and escalates by rule | |
|---|---|---|---|
| Takes actions | No | Suggests, a person acts | Yes, within set limits |
| Memory | This conversation | This session | Persistent, per case |
| Human approval | Not applicable | Always | Configurable per action |
| Audit trail | A transcript | A transcript | Every action, input and decision |
| Integration | None needed | Reads your tools | Reads and writes through scoped APIs |
| Best for | Support and internal knowledge | Speeding up specialists | Running a bounded process end to end |
| Read how we bound autonomy → |
Not sure which one your process needs? The two-week audit answers that before any build starts.
Book the auditHow does AI agent development work?
How do companies use AI agents?
For bounded, rule-heavy work with people in the loop, such as claims triage, regulatory and financial reporting, ticket routing, reconciliations, document intake and customer operations. The agent does the routine steps and a person approves the ones that matter.
What is the AI agent development process?
Audit, design, build, pilot, scale. A two-week use-case audit, a written agent design with tools and guardrails, a build on Amazon Bedrock delivered as code, a supervised pilot with a person approving each action, then autonomy widened by rule as the evaluation passes.
How long does it take to build an AI agent?
About eight weeks to a first agent in production, two for the audit and four to six for design, build and the supervised pilot. Later agents reuse the platform and take less.
How AI agent development works with us
Engineers use AI at every stage. A person approves every action until the evaluation says otherwise.
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Weeks 1 to 2, fixed price
Use-case audit
We pick the first process with you, baseline it and design the guardrails your risk team will ask about. You get a fixed quote for the build.
- ROI model with a baseline
- Agent design with tools, permissions and approval gates
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Weeks 3 to 6
Build on Amazon Bedrock
Tools, memory and integrations are built as code into your AWS account, with an evaluation suite the agent has to pass.
- Agent, integrations and tests as code
- Evaluation suite and results
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Weeks 7 to 8
Supervised pilot
The agent runs on real cases with a person approving each action. Every action, input and decision is logged.
- Pilot report against the baseline
- Rules for widening autonomy
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Ongoing
Run and improve
Cost per task and drift are monitored, and what the agent did is reviewed with the process owner every month.
- Monthly review and cost per task
- The next process scoped from the numbers
Agents you can explain to an auditor
The controls are rules in the design, not promises in a slide.
- Every action logged with its inputs, its decision and its output
- Per action approval gates, tightened or relaxed by rule
- Per task cost tracked, so the business case is checked monthly
- 8 weeks from the start of the audit to a first agent in production
Delivered on Amazon Bedrock and Bedrock AgentCore, under the controls audited for our SOC 2 and ISO 27001 programs.
What are the benefits of AI agent development services?
Why use an AI agent development company?
Because the hard part is not the model, it is the guardrails, the integration and the evidence. A partner that has shipped agents brings the evaluation sets, the approval patterns and the audit trail that let an agent pass a risk review.
What are the key benefits of AI agents?
Routine steps done in minutes instead of days, a consistent process every time, people freed for the decisions that need judgment, and a log that shows exactly what happened for every case.
How do AI agents improve business performance?
By cutting the cycle time and cost of a process without cutting the control over it. It is measured on one process first, with a baseline before and the agent’s numbers after.
Agents we have shipped
All case studies
How Dedicatted Brought Agentic AI to Chemical Reporting at Cassen Laboratories
Dedicatted's agentic AI helped Cassen Laboratories triple chemical analysis capacity and deliver compliant reports in hours, not days
Agentic Voice Automation for the Clinic Revenue Cycle at Spike Technologies
About project The Challenge The expensive part of the work is a conversation. Scripted IVR navigation and portal scraping retrieve a fraction of eligibility answers and break whenever.
GenAI-Powered Claims Processing
How Dedicatted built a GenAI claims adjudication platform for Xodus Travel Services on Amazon Bedrock, cutting manual effort by 70% and lifting adjudicator throughput 85%.
The stack behind our AI agents
Built on AWS first, integrated with the systems you already run.
Models and platform
Foundation models and the agent runtime on AWS, with open models where they fit.
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Amazon Bedrock -
SageMaker -
Hugging Face -
MLflow
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Orchestration
Agent logic, tools and evaluation written as code your team can read.
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LangChain -
Python -
PyTorch
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Data and memory
Case memory, documents and the records an agent reads and writes.
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Amazon S3 -
DynamoDB -
PostgreSQL -
Redis
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Integration
Scoped connections to the systems where the work happens.
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Lambda -
EventBridge -
Kafka -
Salesforce
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Delivery
Environments, pipelines and infrastructure as code.
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Docker -
Kubernetes -
Terraform -
GitHub Actions
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Monitoring and control
Actions, approvals, cost and drift on dashboards you own.
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Datadog -
Grafana -
Prometheus -
PagerDuty
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FAQ
Which platforms do you build agents on?
Amazon Bedrock and Bedrock AgentCore first, because that is where our Agentic AI Specialization and most of our customers run. Agents integrate with the systems you already have through scoped APIs.
How do you stop an agent from doing harm?
Scoped permissions, approval gates per action, an evaluation suite the agent must pass before autonomy is widened, and a full audit trail of every action, input and decision.
How long until a first agent is in production?
About eight weeks. A two-week audit, then four to six weeks of design, build and a supervised pilot with a person approving each action.
What does AI agent development cost?
The audit is a fixed price agreed in the first call. Build and run are quoted from the audit, per agent, with the monthly run cost shown separately from the build.
Do we own the agent?
Yes. The agent, its tools, tests and infrastructure are delivered as code into your repositories and your AWS account. Nothing runs on our infrastructure.
Can an agent work with our existing data platform?
Yes. Agents read and write through your APIs, databases and document stores with permissions scoped to the task. Where the data foundation is not ready, our data and analytics team fixes that first.
How do you use AI in the delivery itself?
Our engineers use AI at every stage, drafting tools, tests, evaluation sets and documentation. Every result is verified by an engineer before it ships, the same way the agent’s own actions are checked.
Do you offer enterprise AI agent development services?
Yes. Enterprise AI agent development services are our main AI work. We build agents for regulated finance, insurance, healthcare and life sciences with scoped permissions, approval gates and a full audit trail, so they pass a risk review.
What is the difference between agentic AI development services and AI agent development?
They are two names for the same work. Agentic AI development services describe the capability, software that plans and acts. AI agent development describes the deliverable, a specific agent for a specific process. Our agentic AI services page covers the capability.
Question not answered? Ask an AI engineer. Same-day reply on feasibility questions.
AI agent development company for enterprise workflows
Dedicatted is an AI agent development company that builds custom AI agents for enterprise workflows on Amazon Bedrock, from agent strategy and use-case audits to custom agent development, integration with CRM, ERP and data platforms, and lifecycle management in production. Our agentic AI services and generative AI services share the same guardrail-first method, delivered by an AWS Premier Tier Services Partner with the Agentic AI Specialization.
Custom AI agent development services
Dedicatted provides AI agent development services for organizations that want software agents to complete bounded business processes end to end, reading records, calling APIs, preparing documents and escalating to a person when a rule says so. Our AI engineers combine agent design, guardrails and evaluation, Amazon Bedrock and AgentCore engineering, systems integration and production monitoring to deliver agents that are explainable, auditable and measured against a baseline.
We support businesses with
- AI agent strategy and use-case audits
- custom AI agent development on Amazon Bedrock
- agentic AI development for finance, insurance, healthcare and life sciences
- integration with CRM, ERP, ticketing and data platforms
- evaluation suites, approval gates and audit trails
- agent lifecycle management with monitoring, cost per task and drift checks
Agentic AI development services
Agentic AI development services cover the design of how an agent plans, which tools it may call, what it remembers and when it must ask a person. We deliver that design in writing before any build, so the risk review happens on paper first.
Enterprise AI agent development services
Enterprise AI agent development services add what a regulated company needs on top of a working agent. Scoped permissions, approval gates per action, an evaluation suite, an audit trail of every action and cost per task reported monthly.
A custom AI agent development company on AWS
As a custom AI agent development company we build on Amazon Bedrock and Bedrock AgentCore, deliver the agent as code into your AWS account and integrate it with your CRM, ERP, ticketing and data platforms through scoped APIs.
Get started with an AI engineer
Tell us which process waits on people today and what it costs. Our team responds within one business day with relevant agents we have shipped and a first read.
Thanks, we have it.
Our team replies within one business day, with relevant experience and a first read on your problem.