Custom Agentic AI Application Development

Build Autonomous AI That Thinks and Acts for Your Business

We design and build agentic AI systems that understand context, make decisions, and run complex workflows with minimal supervision. From startups to enterprises, SDH helps teams move beyond basic automation to scalable, intelligent operations connected with your tools and data.

Multi-Agent Architecture • Tool Use & API Integration • Enterprise-Grade Autonomy
55+ AI & Agentic Experts
Cross-functional, senior engineering team
38+ Delivered AI Systems
Across SaaS, fintech, healthcare & operations
9M+ End Users
Served by our software & AI platforms
19+ Years of
End-to-end Software Development

SDH engineers production-grade AI — from autonomous task agents to multi-agent orchestration systems — built with enterprise-level security, predictable logic, and robust integrations. With 19+ years of engineering excellence, we deliver scalable, maintainable agentic AI solutions for startups, SMBs, and large companies.

What You Get with Agentic AI Systems

We build agentic systems that combine autonomous reasoning, deep integration, and multi-agent collaboration to solve your core operational challenges.

Agentic Reasoning & Autonomous Workflow Automation

AI agents capable of independent reasoning, planning, and adaptive decision-making. We use AutoGen-orchestrated workflows to automate complex multi-step business processes without predefined scripts.

Multi-Agent Collaboration & Distributed Execution

Specialized agents coordinate, delegate tasks, validate outputs, and operate as a unified system — increasing accuracy, reliability, and operational throughput across your workflows.

MCP-Powered Integration Layer

A universal interface (Model Context Protocol) enabling seamless access to APIs, databases, cloud platforms, and internal systems — eliminating the need for custom integration code.

Enterprise Data Intelligence & Knowledge Grounding

Secure retrieval-augmented generation (RAG), structured memory, and enterprise-grade data pipelines ensure every answer is grounded in verified business knowledge.

Enterprise Reliability & Safety

Addresses transparency and auditability challenges through validation layers, compliance checks, audit trails, and human-in-the-loop controls — ensuring safe and predictable AI behavior.

Human Workload Reduction & Role Augmentation

As a direct outcome of intelligent automation, AI agents replace repetitive manual work, accelerate internal processes, reduce operational costs, and allow your team to focus on higher-value contributions.

Each solution is fully customized: from single-agent copilots to complex multi-agent systems for procurement, customer operations, analytics, compliance, and cross-system automation.

Agentic AI Systems Development Services

Flexible engagement levels tailored to your current AI maturity — from rapid MVP validation to full-scale agentic ecosystems powering your operations.

For Startups: Agentic AI MVP

A fast-launch prototype to validate your agentic concept, test feasibility, and demonstrate multi-agent workflows with minimal investment. Perfect for early-stage exploration and rapid innovation.

Starting from $15,000

Production-Ready Architecture: A scalable foundation you can extend into a full product without rebuilding from scratch.

Real Autonomous Behavior: Agents reason, plan, take actions, and collaborate across workflows — not just respond to prompts.

Get the Fast-Track with Special Offer

Agentic Workflow Automation Suite

Structured agentic workflows designed to automate multi-step business tasks, reduce manual effort, and orchestrate actions across tools and APIs.

Starting from $60,000

Multi-step reasoning & task planning
Agent-to-agent communication
Integration with CRM, ERP & business APIs
End-to-end workflow automation
Delivery 10–14 weeks

AI Automation Platforms

Large-scale AI platforms that coordinate multiple agents, share memory, orchestrate tools, and automate cross-department workflows at enterprise scale.

Starting from $90,000

Multi-agent platform architecture
Unified memory & context management
Multi-source & multi-system orchestration
Observability dashboards & logs
Delivery 16–24 weeks

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Fast-Track Agentic AI MVP & Workflow Validation

Before investing in a full-scale autonomous system, the smartest step is to validate the idea with a fast MVP or POC. Modern visual agent frameworks allow us to prototype multi-agent workflows, tool-calling logic, and automation sequences in days — not months. This reduces risks, accelerates decision-making, and proves business value early.

How We Deliver Your Fast-Track MVP

We Use Innovative Agentic AI Tools & Frameworks. These platforms allow us to build and validate agent workflows, reasoning chains, integrations, and automations with exceptional speed — delivering working MVPs in days.

5–10 Day Initial Prototype

A reasoning-ready prototype that demonstrates agent logic and system interaction almost immediately.

2–3 Week Workflow Validation

Rapid modeling of real business processes with agent coordination, RAG, and tool usage.

Risk-Free Try-Before-Scale

Validate feasibility early, secure stakeholder approval, and reduce investment risk before full product development.

Special Offer: Up to 50% Co-Financing for Agentic AI MVPs

SDH Global launches a special program for businesses and startups looking to validate agentic AI ideas quickly. With up to 50% co-financing for early-stage MVP development, you can test automated workflows, reasoning loops, integrations, and multi-agent logic at a fraction of the cost — and bring your innovation to market faster.

Learn More Details

Case Studies: Agentic AI in Action

A few examples of how we design and deploy agentic AI systems that automate complex workflows, reduce operational load, and deliver measurable ROI.

Advanced Architectures for Your Industry

Agentic AI systems require domain-specific design. Each industry needs its own orchestration logic, compliance boundaries, data flows, and multi-agent coordination patterns. Explore how SDH builds production-ready agentic architectures optimized for real workflows.

Operations & Procurement: Autonomous Multi-Step Execution

Procurement workflows rely heavily on manual checks, email communication, inventory status, and vendor coordination. Agentic AI replaces fragmented steps with a coordinated multi-agent system capable of planning, validating, executing, and monitoring end-to-end procurement flows.

Typical Architecture: Planner Agent → Data Retrieval Agent → Vendor Analysis Agent → API Automation Agent (ERP / CRM) → Validation Agent → Reporting Agent.

The system autonomously checks stock levels, compares vendors, drafts purchase orders, triggers approvals, and logs actions into ERP — reducing cycle times and human involvement.

Typical Outcomes

  • Procurement cycle time reduced by 35–55%
  • Fewer manual errors and duplicated work
  • Improved vendor insights & decision quality
  • End-to-end audit trail for compliance

Ideal for manufacturing, retail, distribution, and enterprise operations teams managing complex approvals and supplier ecosystems.

Customer Support & CX: Autonomous AI Agents for End-to-End Service

Traditional chatbots handle only surface-level conversation. Agentic systems orchestrate reasoning, knowledge retrieval, workflow execution, and back-office integrations — delivering real resolution rather than scripted responses.

Architecture Example: Conversation Agent → Knowledge Agent → Tool-Use Agent → CRM/ERP Integration Agent → QA Agent.

The AI understands intent, verifies policy rules, retrieves precise answers, performs actions (refunds, updates, routing), and validates results — delivering measurable improvements in customer satisfaction and operational speed.

Typical Outcomes

  • Support workload reduced by 40–65%
  • Higher CSAT via context-aware responses
  • Autonomous resolution for routine requests
  • Full auditability for quality teams

Ideal for e-commerce, SaaS, telecom, banking CX, logistics, and marketplaces.

Finance & Compliance: Risk-Aware Autonomous Agents

Regulatory teams analyze thousands of pages of rules and internal policies. Agentic AI orchestrates validation workflows, cross-checking documents, logs, and rules to generate accurate compliance verdicts and audit-ready outputs.

Architecture: Meta-Agent → Compliance Agent → Document Analysis Agent → Risk Agent → Reporting Agent.

The system flags violations, extracts relevant evidence, verifies rules, and prepares full compliance summaries — drastically reducing review time and improving consistency.

Typical Outcomes

  • Compliance checks delivered 50–70% faster
  • Lower audit risks and human errors
  • Automated extraction of critical facts
  • Secure, role-based access & logging

Perfect for finance, insurance, banking, fintech, and enterprise governance teams.

Manufacturing & Supply Chain: Predictive & Autonomous Pipelines

Manufacturing relies on highly coordinated processes: scheduling, inventory, quality checks, machine data, and logistics. Multi-agent architectures enable prediction, anomaly detection, and autonomous decision execution across the full pipeline.

Architecture: Sensor Agent → Forecasting Agent → Anomaly Agent → Optimizer Agent → Execution/ERP Agent.

From quality scoring to production planning, agentic systems anticipate issues, adjust schedules, and execute actions through ERP/MES systems.

Typical Outcomes

  • Production delays reduced by 20–40%
  • Lower scrap & defect rates
  • Optimized inventory & logistics
  • Real-time operational visibility

Relevant for manufacturing plants, logistics networks, and industrial operations.

SaaS & Product Companies: Agentic Features Inside Your Platform

SaaS teams compete on speed and customer experience. Agentic AI introduces autonomous onboarding, problem-solving, configuration, troubleshooting, and product intelligence built directly into your platform.

Example Workflow: Onboarding Agent → Troubleshooting Agent → Documentation Agent → Usage Analytics Agent.

Agents understand user intent, retrieve product knowledge, diagnose issues, execute in-app actions, and guide users step-by-step — increasing product adoption and reducing support load.

Typical Outcomes

  • Support requests down 30–50%
  • Faster onboarding and activation
  • Improved product adoption & retention
  • Higher customer satisfaction

Perfect for SaaS, devtools, B2B software, mobile apps, and product-led companies.

Healthcare & Life Sciences: Safe, Validated Decision Pipelines

Medical and clinical workflows are high-risk and slow due to manual reviews, protocols, and compliance constraints. Agentic AI provides controlled autonomy with strict accuracy, traceability, and compliance boundaries.

Architecture: Clinical Query Agent → Data Extraction Agent → Guideline Matching Agent → Safety/Validation Agent → Explanation Agent.

The pipeline ensures the AI never invents clinical advice — every recommendation is grounded in validated protocols and cross-checked across multiple agents.

Typical Outcomes

  • Clinical decision prep 40–60% faster
  • Reduced risk through multi-agent cross-validation
  • Consistent application of guidelines
  • Structured data for EMR/EHR systems

Ideal for hospitals, diagnostics, insurance, medtech, and life sciences research.

How We Work: Agentic AI Development Process

Building an agentic AI system requires more than engineering — it requires orchestration, iterative reasoning design, safety boundaries, and seamless integration. Our process blends strategic discovery, modular architecture, and production-grade implementation tailored to your real business needs.

Strategy & Consultation

We begin by analyzing your processes, data flows, tasks, and automation opportunities to map out agent roles, tool capabilities, and expected performance outcomes.

Outcome: A clear vision for your agentic AI system, aligned with measurable business goals.

Data Preparation

We structure, clean, and enrich operational data to support accurate reasoning, retrieval, and decision-making across agents.

Outcome: High-quality, unified data ready for multi-agent workflows.

Multi-Agent System Design

We define agent roles (planner, reasoning, tool-use, validator, integration), communication protocols, safety layers, and workflow orchestration patterns.

Outcome: A modular, scalable agentic architecture built around your operational logic.

Vector & Knowledge Layer Setup

Configuration of vector databases, embeddings, document pipelines, and high-relevance retrieval for agent reasoning and evidence-based decision-making.

Outcome: A dependable knowledge foundation powering accurate agent actions.

LLM Integration & Prompt Engineering

Integration with leading LLMs and refinement of prompts, instructions, and agent communication templates to ensure consistent, controllable reasoning.

Outcome: A stable interaction layer enabling smart, predictable autonomous behavior.

Application Development

UI/UX, dashboards, automation interfaces, admin consoles, and workflow modules built to support your internal teams and end-users.

Outcome: A polished application that makes agent capabilities accessible and practical.

System Integration

Secure integration with CRMs, ERPs, APIs, internal tools, and data systems. Agents gain real execution capabilities, not just conversation.

Outcome: Agentic AI seamlessly embedded into your existing workflows and platforms.

Testing, Deployment & Monitoring

Rigorous QA, scenario testing, safety validation, and ongoing monitoring ensure agent reliability and predictable autonomy in production.

Outcome: A stable production system with transparent agent behavior and performance tracking.

Knowledge Transfer & Support

We train your team, deliver documentation, refine workflows, and provide continuous improvement for scaling new agent capabilities.

Outcome: A self-sufficient organization equipped to evolve its agentic AI ecosystem.

Our Advanced Tools & AI Engineering Stack

Powerful frameworks, runtimes, and integrations that enable scalable, production-ready agentic AI systems.

Fast api
Flask
Javascript
AWS
Java
Typescript
Flutter
Terraform
Postgresql
Kafka
Kotlin
C
Objective-c
MongoDB
Swift
Redux
Vue
React
RabbitMQ
Python
Python-s
Docker
Jenkins
Django
Swift
Redux
Vue
MongoDB
Docker
Jenkins
Django
Java
Typescript
Flutter
Terraform
Postgresql
Kafka
Kotlin
C
Objective-c
Fast api
Flask
Javascript
AWS
React
RabbitMQ
Python

AI Models & Reasoning Engines

OpenAI GPT Family Anthropic Claude Google Gemini Meta LLaMA Mistral DeepSeek R1 HuggingFace LLMs

Vector Databases & Knowledge Systems

Pinecone Weaviate Milvus FAISS Redis Vector pgvector (Postgres) Elasticsearch

Agentic Frameworks & Orchestration

LangGraph AutoGen CrewAI OpenAI Swarm LlamaIndex DSPy Hugging Face Transformers

Cloud & Infrastructure

AWS / Azure / Google Cloud Kubernetes, Docker, Helm Terraform, Ansible Cloud Functions & Serverless CI/CD: GitHub Actions, Jenkins Load Balancing & Auto-Scaling

Monitoring, Observability & MLOps

MLflow Weights & Biases (W&B) EvidentlyAI Arize AI Prometheus Grafana Guardrails AI

Integration Modules & APIs

REST / GraphQL APIs CRM: HubSpot, Salesforce ERP: SAP, Odoo, MS Dynamics Task Tools: Jira, Asana, Trello Messaging: Slack, Teams, Email RPA & Automation Pipelines Database Drivers (SQL/NoSQL)
Our team
Our team
Our team

Ready to build your next-generation Agentic AI system?

Let’s turn your workflows, data, and processes into fully autonomous multi-agent capabilities — designed for real business impact, not just experimentation.

From strategy and architecture to integrations and production deployment, our team helps you build secure, scalable, and high-performance agentic AI applications that deliver measurable value from day one.

Frequently Asked Questions

Answers to the most common questions about agentic AI systems, integrations, safety, and delivery timelines.

Agentic AI is not just a conversational interface — it is a system capable of reasoning, planning, taking action, using tools, and coordinating multiple autonomous components. A chatbot answers questions, while an agent can execute workflows, trigger automations, call APIs, and solve tasks end-to-end.

Agentic AI can automate research, reporting, customer service, document processing, data enrichment, CRM/ERP actions, decision flows, task routing, quality assurance, and multi-step operational workflows. Multi-agent setups handle complex scenarios involving multiple systems and teams.

We design agentic systems with strict guardrails: tool whitelists, rule-based constraints, isolated execution environments, role-based access, audit logs, and configurable safety policies. Agents operate within clearly defined boundaries and cannot exceed approved workflows or permissions.

For early stages, all you need is a clear business goal and a few representative examples of tasks. For advanced systems, we typically use documents, APIs, operational data, business rules, or your CRM/ERP systems. We can start with a lightweight MVP and scale as your data ecosystem grows.

Thanks to modern prototyping tools (Google ADK, OpenAI Workflows, Prompt Flow, n8n, Flowise), a functional MVP can be ready in 5–15 days. A production system with integrations usually takes several weeks, depending on complexity and infrastructure.

Yes. Agentic AI excels at system integration. We support REST/GraphQL APIs, cloud platforms, DBs, microservices, enterprise software, and automation tools. Agents can read data, take actions, trigger workflows, and synchronize information across your ecosystem.
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