Single-Task Agents
We build focused agents that reliably automate one well-defined job end to end.
- Task scoping and design
- Tool and API connection
- Evaluation and guardrails
AI Agent Development Services
AI Agent Development Services
Trusted across 20+ countries by Fortune 500 companies and growth-stage brands
We build AI agents that reason, plan and take action across your tools, completing multi-step tasks with minimal supervision. From single-task agents to multi-agent systems, every build is engineered for production and measurable outcomes. Over a decade of experience, 250+ digital solutions delivered.
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What is AI agent development?
AI agent development is the engineering of autonomous AI systems that can reason, plan and execute multi-step tasks across your business tools, going beyond generating a single response. Noseberry builds single-task agents, ReAct agents, multi-agent systems and memory-augmented agents using frameworks like LangGraph and AWS Bedrock Agents, with guardrails and human oversight built in for safe production use.
Key takeaways
- AI agents reason, plan and act across tools, unlike generative AI that responds to a single prompt.
- We build single-task, ReAct, multi-agent and memory-augmented agents.
- A proof of concept ships in 2 to 4 weeks, a production-ready agent in 4 to 6 weeks.
- Every agent includes guardrails and human-in-the-loop controls for safe operation.
2M+Lives touched
15+Fortune 500 clients
20+Countries served
250+Digital solutions delivered
What we build
Our AI agent development services
ReAct Agents
We build agents that reason and act in a loop, deciding the next step based on results.
- Reasoning and action orchestration
- Dynamic tool selection
- Error handling and retries
Multi-Agent Systems
We build teams of agents that coordinate to complete complex, cross-system workflows.
- Agent orchestration and roles
- Inter-agent communication
- Workflow supervision
Memory-Augmented Agents
We build agents that retain context across sessions for more capable, personalised behaviour.
- Short and long-term memory
- Context and state management
- Personalisation
Agent Tooling and Integration
We connect agents to your systems so they can act, not just advise.
- ERP, CRM and legacy connectivity
- API and function calling
- Event-driven triggers
Guardrails and Human Oversight
We build the controls that keep autonomous agents safe and accountable.
- Human-in-the-loop approvals
- Output guardrails and policy checks
- Monitoring and audit trails
Where it delivers value
Where AI agents deliver value
Insurance
process claims end to end.
Real estate
automate tenant onboarding.
Supply chain
automate ordering and decisions.
Customer support
resolve tickets across systems.
Operations
automate repetitive multi-step back-office work.
How we work
Our five-phase process
You see a working proof of concept early, before committing to a full build.
1
Discovery and Audit
We map your tools, data and goals to understand where you stand today.
2
Strategy and Roadmap
We prioritise use cases and hand you a costed, phased plan.
3
Rapid Proof of Concept
We validate the highest-value agent fast, with clear success metrics.
4
Build and Integrate
We engineer and connect the agent into your production stack.
5
Deploy and Optimize
We ship, monitor and tune, so value compounds after launch.
Models and technology we use
Agent frameworks
- LangGraph
- AWS Bedrock Agents
- LangChain
Models & LLMs
- OpenAI GPT
- Anthropic Claude
- Llama
- Mistral
- Gemini
Data & vector
- Snowflake
- Databricks
- Pinecone
- Weaviate
- Kafka
- Spark
Cloud AI & MLOps
- AWS Bedrock & SageMaker
- Azure AI
- Google Vertex AI
- Docker
- Kubernetes
Security and compliance
Safe agents, by design
Security and responsible AI are built in from day one, including guardrails on agent actions, private hosting, encrypted data pipelines, role-based access controls and human-in-the-loop approvals for sensitive steps. We build to GDPR, HIPAA and SOC 2, deployed on AWS, Google Cloud and Azure with monitoring and audit trails.
GDPRHIPAASOC 2
Real success storiesFinTech · Digital Insurer PropTech · Real-estate marketplace E-Commerce · Retail leader
Outcomes we have driven
Challenge
Claims handling needed multi-step judgement across several systems.
Solution
A tool-using agent that gathers documents, checks policy and routes exceptions for approval.
Impact
93% of fraud caught pre-payout, an estimated $4.2M saved annually.
Challenge
Tenant onboarding was manual and spanned many tools.
Solution
A multi-agent workflow that automates intake, checks and follow-ups.
Impact
40% faster onboarding and valuations with higher consistency.
Challenge
Support tickets required actions across CRM, orders and catalogue.
Solution
An agent that resolves tickets end to end with human handoff on edge cases.
Impact
+28% lift in conversion from freed-up team capacity.
Sector-anonymised outcomes shown until named clients are approved.
Why Noseberry
Why choose Noseberry for AI agent development
Specialist
AI, Cloud and Data is our core, no generalist dilution.
Production-first
We build agents that reach production, with the guardrails to run safely.
Vendor-neutral
We choose the right frameworks and models on fit, cost and risk.
Proven at scale
2M+ lives touched, 15+ Fortune 500 clients, 250+ solutions across 20+ countries.
Engagement options
Our scalable engagement options
01
End-to-End Project Ownership
Full lifecycle from discovery to deployment and optimisation.
02
AI Expertise on Demand
Fractional access to senior AI agent engineers and data scientists.
03
Milestone-Based Collaboration
Defined deliverables like an agent PoC or integration, with fixed timelines.
04
AI Innovation Lab as a Service
Prototype and validate agent ideas fast in a sandbox.
05
AI Maintenance & Optimization Retainer
Monitoring, tuning and optimisation after launch.
AI agents, answered.
An AI agent is an autonomous system that can reason, plan and execute multi-step tasks across your tools with minimal human supervision, going beyond generating a single response.
A chatbot responds to prompts. An AI agent takes action, completing end-to-end workflows across your systems, deciding the next step based on results.
Single-task agents, ReAct agents, multi-agent systems and memory-augmented agents, using frameworks like LangGraph and AWS Bedrock Agents.
A proof of concept ships in 2 to 4 weeks, a production agent in 4 to 6 weeks, and a full multi-agent system in 12 to 20 weeks.
Through guardrails on actions, human-in-the-loop approvals for sensitive steps, policy checks, monitoring and audit trails.
Yes. We connect agents to your ERP, CRM and legacy systems through APIs and function calling so they can act, not just advise.
Ready to put AI agents to work?
Book your free 30-minute AI strategy session and we will scope an agent use case and the fastest path to production.
Book nowRelated resources
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