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LangGraph Β· CrewAI Β· Tool Use Β· Human-in-Loop

πŸ€– AI Agents
That Act. That Automate. That Deliver.

AI that takes actions, not just answers questions. We build production-grade autonomous agents that interact with your APIs, databases, and systems to automate complex multi-step workflows β€” end to end, with enterprise safety guarantees.

Start Your Project β†’ Book Free Discovery Call
80%
Time Saved on Workflows
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4.9 / 5.0
HITL
Checkpoints Included
Full
Audit Trail
services/ai/agent-graph.py
from langgraph.graph import StateGraph
# Autonomous research + report agent
graph = StateGraph(AgentState)
graph.add_node("researcher", research_web)
graph.add_node("analyst", analyse_data)
graph.add_node("writer", write_report)
graph.add_node("reviewer", human_review)
graph.add_edge("researcher", "analyst")
graph.add_conditional_edges(
"analyst", route, {"write": "writer"})
# Avg task completion: 4.2 min
What We Build

Every agentic workflow,
automated safely

From single-task automation to complex multi-agent orchestration β€” we build production-safe AI agents with explicit guardrails, full audit trails, and human-in-the-loop checkpoints for high-stakes decisions.

Discuss Your Project β†’
  • β†’Multi-step business process automation end-to-end
  • β†’API and database tool use with full error handling and retry logic
  • β†’Autonomous web research and data synthesis pipelines
  • β†’Email drafting, triage, and CRM update automation agents
  • β†’Code review, test generation, and documentation agents
  • β†’Multi-agent orchestration with LangGraph and CrewAI frameworks
  • β†’Human-in-the-loop approval gates for critical or irreversible actions
  • β†’Complete audit trail and action rollback capability included
Services Breakdown

Full-spectrum
agentic AI engineering

Every layer of an agentic AI system β€” from tool definitions to multi-agent orchestration β€” with enterprise safety and observability built in from day one.

βš™οΈ
Workflow Automation
LangGraph Β· APIs Β· Databases

Multi-step business process automation replacing manual workflows β€” calling APIs, writing to databases, and handling exceptions.

  • Multi-step workflow automation end-to-end
  • REST API and database tool integration
  • Conditional logic, branching, and loops
  • Exception handling and human escalation
πŸ”¬
Research & Analysis Agents
Web Β· Documents Β· Data Β· Synthesis

Autonomous agents that browse the web, read documents, and synthesise findings into structured reports in minutes.

  • Autonomous web research and fact-checking
  • Competitor monitoring and alerting pipelines
  • Long-document summarisation at scale
  • Structured data extraction from any source
πŸ“§
Communication & CRM Agents
Email Β· Slack Β· HubSpot Β· Salesforce

Agents that draft emails, triage inboxes, generate meeting briefs, and keep your CRM up-to-date without human touch.

  • Email drafting, summarisation, and routing
  • Meeting prep and follow-up generation
  • CRM record enrichment and updates
  • Slack and Teams notification automation
πŸ› 
Dev & Code Agents
GitHub Β· CI/CD Β· Tests Β· Docs

AI agents in your development workflow to automate code review, generate tests, and update documentation.

  • Automated code review and suggestions
  • Unit and integration test generation
  • API documentation generation pipelines
  • CI/CD quality gate integration
πŸ‘₯
Multi-Agent Systems
Orchestrator Β· Specialists Β· Parallel

For complex workflows, we build multi-agent systems with an orchestrator delegating to specialist sub-agents for throughput.

  • LangGraph stateful agent graph design
  • CrewAI task delegation frameworks
  • Parallel agent execution for throughput
  • Supervisor and specialist agent patterns
πŸ›‘
Safety & Observability
HITL Β· Audit logs Β· Rollback Β· Guards

Production agents require enterprise safety. We build approval gates, audit trails, rollback capability, and hard guards.

  • Human-in-the-loop approval checkpoints
  • Complete audit trail of every action
  • Action rollback and state recovery
  • Hard tool access limits and guardrails
Technology

The stack behind every AI Agent project

Best-in-class tools chosen for performance, reliability, and team expertise β€” not hype.

LangGraphCrewAILangChainPythonFastAPIPostgreSQLRedisAWS LambdaSendGridCal.comAuth0LangSmithWeights & BiasesGitHub API
Our Process

Brief to deployed β€” how we work

A clear, collaborative process with no surprises and working demos at every milestone.

01
Task Decomposition
Week 1

Map the target workflow step by step. Identify automation candidates, human approval points, and required tool integrations.

02
Tool Integration
Week 1–3

Build the tool suite: API wrappers, database connectors, search tools, and custom actions the agent needs.

03
Agent Architecture
Week 2–4

Design the agent graph (LangGraph or CrewAI), planning loops, error handling, and human-in-the-loop checkpoints.

04
Testing & Red-Teaming
Week 3–5

Adversarial testing for unexpected tool use, infinite loops, and edge cases. All failure modes tested explicitly.

05
Observability Setup
Week 4–6

Full action logging, LangSmith tracing, Slack failure alerts, and an operator dashboard for live oversight.

06
Production & Iteration
Week 6–8

Deploy with human-in-the-loop where required, monitor success rates, and iteratively expand capabilities.

Why Nexcode

What sets our AI Agent work apart

πŸ—
Senior Engineers Only

No juniors, no mid-weight delegation. Every engineer on your project is 5+ years experience, senior by any measure.

⚑
Performance as Pass/Fail

We set Lighthouse 90+ as a non-negotiable acceptance criterion β€” not a target, a requirement. Deployments fail if CWV regress.

πŸ§ͺ
Test Coverage Standard

Unit, integration, and E2E tests as standard deliverable. We don't ship without coverage. No exceptions under deadline pressure.

πŸ“
Architecture Before Code

Full system design β€” schema, API contracts, auth, deployment β€” documented and approved before any code is written.

β™Ώ
Accessibility Built-in

WCAG 2.1 AA from component 1, not added at the end. Keyboard navigation, screen readers, colour contrast β€” non-negotiable.

πŸ”
Weekly Working Demos

End of every sprint, you get a live staging URL to click through. Not a Loom recording β€” a real deployed demo.

πŸ”’
Zero Lock-in Guarantee

100% IP & code transfer. Your repo, your infra, your AWS account. Full documentation so your team can own it the day we hand over.

πŸ“Š
Analytics-Ready Launch

GA4, Mixpanel or Amplitude wired in before go-live. You launch with data, not waiting weeks to set up tracking after.

How we compare
Criteria ✦ Nexcode Typical Agency Offshore Dev Shop Freelancer
Full IP & code ownershipβœ“βœ“βœ“βœ“
Client Reviews

What clients say about our AI Agent work

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4.9 / 5.0 Β· 50+ AI projects
"

Nexcode rebuilt our entire frontend in Next.js App Router in 12 weeks. Lighthouse score went from 41 to 97. The code quality, test coverage, and documentation are unlike anything I've ever received from an external team. We extended the engagement twice.

SM
Sarah Mitchell
CTO, Apex Financial Β· SaaS Platform Rebuild
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Upwork Verified
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"They architected and built our entire web platform from scratch β€” real-time collaboration, complex permissions, WebSockets. Every edge case handled, zero bugs at launch."

JK
James Kowalski
CEO, NovaBrain AI
AI Web Platform
β˜…β˜…β˜…β˜…β˜…

"Our new storefront loads in 0.8s and converts at 3.2x our old Magento site. Every detail considered β€” mobile-first, accessibility, structured data. The results speak."

RP
Rachel Patel
Director, LuxeCommerce
Headless eCommerce
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"From Figma to deployed in 8 weeks. Their React architecture thinking sets them apart from every agency I\"

TN
Thomas Nguyen
Founder, WanderGo
Travel Booking Platform
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"200K concurrent users on launch day β€” not a single outage. The infrastructure and caching strategy Nexcode built handled load I didn\"

LM
Laura MΓΌller
VP Product, EduPath
EdTech LMS
β˜…β˜…β˜…β˜…β˜…

"The real-time dashboard processes 1M+ events/day without a hiccup. Clean code, exceptional docs, and they explained every architectural decision. Extended the team afterward."

AK
Amir Khan
CTO, SwiftFreight
Logistics Dashboard
FAQ

AI Agents questions
answered

Have a question not covered here? Book a free 30-min call β†’

What is the difference between an AI agent and a chatbot?↕
A chatbot responds to questions in a conversation. An AI agent takes actions: calling APIs, writing to databases, running code, browsing the web, and chaining multiple steps to complete a complex task autonomously. Think of a chatbot as an assistant that answers β€” an agent as an assistant that works.
Are AI agents reliable enough for production use?↕
Yes β€” with the right design. We build agents with explicit human-in-the-loop checkpoints for high-stakes actions, full audit trails, rollback capability, and hard limits on tool access. We always start with a tightly constrained scope and expand as reliability is proven in production.
What workflows are AI agents best suited for?↕
Agents excel at multi-step workflows with a defined process: research and synthesis, data extraction and entry, document review and classification, and communication automation. They work best when there is a clear definition of success for each step.
What does an AI agent project cost?↕
Single-workflow automation agent from Β£15,000. Multi-step research or communication agent from Β£22,000. Multi-agent orchestration system from Β£35,000. All include production deployment, monitoring, and 30 days post-launch support.
Related Services

Often paired with AI Agents

🧠
Model backbone
β†’
πŸ”
Knowledge retrieval
β†’
βš™οΈ
Agent deployment ops
β†’
πŸ“
NLP & Text AI
Language understanding
β†’
πŸ€–

Automate your most complex workflows with AI agents.

Free agent scoping call. We map your workflow, identify the right agentic architecture, and provide a fixed-price proposal within 48 hours.

Get a Free AI Scoping Call β†’ View All AI Services