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Agentic AI Services

AI that acts,
not just answers.

We build intelligent agent systems that plan, reason, and execute autonomously completing complex workflows so your teams focus on what matters most..

10×
Faster task completion vs manual workflows
85%
Reduction in repetitive decision overhead
24/7
Continuous autonomous operation
5+
Industries actively transformed
Core services

What we build for you

From single-purpose agents to full enterprise deployments — our services cover every layer of the agentic AI stack.

Custom agent development

Purpose-built AI agents tailored to your processes, trained on your data, integrated with your tools and workflows.

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🔗

Multi-agent orchestration

Networks of specialized agents that collaborate, delegate subtasks, and coordinate to solve complex problems no single agent could handle.

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🏢

Enterprise AI consulting

Strategic guidance from readiness assessment and architecture design to governance frameworks and change management.

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🤖

Agentic AI automation

Replace brittle RPA scripts with adaptive agents that understand context, handle exceptions, and improve autonomously over time.

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Industries

Deployed across every sector

Agentic AI automation is transforming operations where speed, precision, and scale matter most.

Customer service Supply chain Healthcare Financial services Software development
Customer service

Autonomous resolution of complex queries, escalation routing, and sentiment-aware responses at scale.

Supply chain

Real-time demand forecasting, supplier negotiation agents, and disruption response automation.

Healthcare

Clinical documentation, prior authorizations, patient triage, and care pathway optimization.

Financial services

Fraud detection pipelines, regulatory compliance agents, and intelligent loan processing workflows.

How it Works

From concept to deployment

Our proven delivery model gets intelligent agents to live in your environment quickly with minimal disruption and maximum control.

01

Discovery & process mapping

We audit your existing workflows, identify high-value automation opportunities, and assess technical readiness for agentic AI deployment.

02

Agent architecture design

Our engineers design the agent topology selecting the right models, tools, memory systems, and orchestration patterns for your use case.

03

Custom build & integration

Agents are built, fine-tuned if needed, and integrated with your existing CRMs, ERPs, databases, APIs, and internal tools.

04

Deploy, monitor & optimize

Production deployment with observability dashboards, human-in-the-loop controls, and ongoing performance optimization to compound ROI over time.

40+
Agentic AI systems deployed across enterprise & scale-up clients
70 - 85%
Average task automation rate across production deployments
300+
API integration services delivered
98%
Client retention rate across all engagements
Client stories

What Our Clients Say

Outcomes from real agentic AI services and AI integration engagements.

"

Built an intelligent agent that handles our entire sales research workflow — prospecting, enrichment, CRM updates, and outreach drafting. We've automated 80% of a 4-person team's manual work.

Ankit Prasad
VP Sales Ops, FinStream
"

The data pipeline they built transformed how our learning agent accesses real-time inventory and pricing. The Kafka streaming pipeline means our agents always have current context — 40% better recommendation accuracy.

Meera Krishnan
Head of AI, RetailCo
"

They were the first team that actually understood the observability requirements — the OpenTelemetry tracing across our multi-agent system gave us visibility we didn't know was possible.

David Saunders
CTO, BuildCorp
Technology stack

Built on frameworks that power production AI

We pick the right tools for your use case, not the ones we're most comfortable with.

Agent frameworks
LangChain LangGraph CrewAI AutoGen ReAct Semantic Kernel
LLM providers
GPT-4o Claude Gemini Llama 3 Mistral AWS Bedrock Azure OpenAI
Vector / memory
Pinecone Weaviate Qdrant ChromaDB pgvector Redis Vector
Data pipelines
Kafka Airflow dbt Databricks Snowflake BigQuery
Cloud infra
AWS Azure Google Cloud Docker Kubernetes Terraform

FAQ

What are agentic AI services?

Agentic AI services involve building autonomous AI agents that can plan, reason, use tools, and complete multi-step tasks with minimal human intervention. Unlike simple AI chatbots, agentic AI systems can call APIs, query databases, write and execute code, browse the web, and orchestrate complex workflows end-to-end. The ‘agentic’ part means they act  not just respond.

What is the difference between a learning agent AI and an intelligent agent AI?

A learning agent AI continuously improves its behaviour based on feedback, experience, or new data — using techniques like RLHF, fine-tuning, or RAG with an updated knowledge base. An intelligent agent AI refers more broadly to any AI system that perceives its environment, reasons about goals, and takes autonomous actions. In practice, most production intelligent agent AI systems also incorporate learning mechanisms — the two terms frequently overlap.

What does AI integration services cover?

AI integration services cover connecting AI models and agents to your existing business systems including API integration services (REST, GraphQL, webhooks), application integration services (CRMs, ERPs, SaaS tools), data pipeline integration services (ETL, streaming, feature stores), and model deployment and runtime integration services. The goal is to make your AI agents genuinely useful within your technology estate, not isolated from it.

What are data pipeline integration services?

Data pipeline integration services involve designing and building the data flows that feed AI agents and models — including ingestion from source systems, transformation, enrichment, vector embedding pipelines for RAG memory, and real-time streaming pipelines that give agents access to live business context. Without solid data pipeline integration, even the best intelligent agent AI will be operating on stale or incomplete information.

What is model deployment and runtime integration?

Model deployment and runtime integration services cover everything needed to run AI models reliably in production — containerisation, serving infrastructure (REST endpoints, streaming), A/B testing and canary deployments, autoscaling, latency optimisation, and integration with orchestration frameworks like LangGraph and CrewAI. We also instrument every deployment with OpenTelemetry for full observability across all agent spans and tool calls.

What frameworks do you use for agentic AI development?

We build agentic AI services using LangChain, LangGraph, CrewAI, AutoGen, and custom frameworks depending on the use case. For model deployment and runtime integration we use AWS Bedrock, Azure OpenAI, and self-hosted open-source models (Llama, Mistral). For data pipeline integration services we use Apache Kafka, Airflow, dbt, and vector stores including Qdrant, Pinecone, and Weaviate. Framework choice is always driven by your requirements, not our preferences.

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Stay informed about the latest trends, best practices, and insights in logistics and supply chain management. Our blogs cover a wide range of topics, from the impact of AI on logistics to the future of smart warehouses. Explore our blog section to access valuable information that can help you navigate the evolving landscape of logistics and supply chain management.