01
AI Sales Development Rep
Researches leads, sends hyper-personalized outreach emails, handles objections, and books discovery calls on your calendar — fully autonomous.
LangChainGPT-4oHubSpot
Agentic AI Development
AI Agents That Think, Plan & Execute
We build production-grade autonomous AI agents using LangChain, LangGraph, AutoGen, and CrewAI. Deploy digital workers that handle complex multi-step tasks end-to-end — without human intervention.
From AI sales reps to autonomous research agents — we design, develop, and deploy agentic AI systems tailored to your exact business workflow.
10x
Faster task execution
24/7
Autonomous operation
80%
Reduction in manual work
$1K
Starting project cost
01The Key Difference
Chatbots Talk. Agents Do.
Traditional chatbots respond to queries. Agentic AI systems receive a goal and autonomously determine the steps, tools, and decisions needed to achieve it. They don't just answer — they act.
Using frameworks like LangGraph and CrewAI, we build agents that plan, reason, use tools, self-correct, and complete complex workflows in a single run.
- 01Multi-step task execution with memory
- 02Tool use: web search, APIs, databases, code execution
- 03Self-correction and error recovery loops
- 04Human-in-the-loop checkpoints when needed
Without AI Agent
Marketing team manually researches 50 leads, writes individual emails, logs to CRM — 8 hours per week.
With AI Agent
Agent researches, personalises, sends, tracks, and logs — 8 hours of work done in 12 minutes. Every day.
Standard Chatbot
Customer asks a complex question — chatbot says "I'll transfer you to an agent."
Agentic AI
Agent checks account, verifies policy, issues refund, and follows up — all in 30 seconds, 24/7.
02What We Build
Agentic AI Use Cases
02
Autonomous Research Agent
Scours the web, aggregates data from multiple sources, synthesizes insights, and delivers structured reports daily — no human in the loop.
LangGraphTavilyNotion
03
AI Customer Resolution Agent
Handles Tier-1 & Tier-2 support tickets using RAG, accesses your internal tools, issues refunds, and escalates only genuine edge cases.
RAGZendeskSlack
04
Data Analysis & Reporting Agent
Pulls data from your CRM, analytics platforms, and databases — runs analysis, generates boardroom-ready reports, and emails them on schedule.
PythonBigQuerySheets
05
Supply Chain Monitoring Agent
Monitors stock levels, vendor updates, and delivery ETAs. Creates draft POs when inventory drops below threshold and alerts your ops team.
n8nShopifySlack
06
Content Production Agent
Generates SEO-optimized blog drafts, social posts, and email campaigns aligned to your brand voice — reviewed, scheduled, and published automatically.
LangChainWebflowBuffer
03Tooling
Our Agentic AI Tech Stack
LangChainLangGraphAutoGenCrewAIOpenAI GPT-4oAnthropic ClaudePineconeWeaviaten8nPython
04Process
Our Agentic AI Development Process
01
Discovery & Workflow Mapping
We audit your operations, identify the highest-ROI agentic opportunities, and define agent goals, tools, and success metrics.
02
Architecture Design
We design the agent graph — nodes, tools, memory stores, human-in-the-loop checkpoints — before writing a single line of code.
03
Build & Integrate
We build the agent using LangChain/LangGraph/CrewAI and integrate it with your CRM, APIs, databases, and communication channels.
04
Testing & Red-Teaming
We put the agent through adversarial testing, edge case simulations, and real production scenarios to eliminate failure modes.
05
Deploy & Handoff
We deploy, monitor for 30 days, train your team, and provide documentation. Ongoing support available.
05FAQ
Frequently Asked Questions
01
What industries do you build agentic AI for?
We build agentic AI systems for SaaS, e-commerce, recruitment, real estate, healthcare admin, legal, finance, and professional services. If you have a repeatable workflow with decisions, an agent can handle it.
02
What's the difference between an AI agent and an automation workflow?
Traditional automation (Zapier, n8n) follows fixed if-this-then-that rules. Agentic AI can reason, adapt, use multiple tools dynamically, and handle novel situations — much closer to how a human employee thinks.
03
How long does it take to build a custom AI agent?
Simple single-purpose agents take 2–3 weeks. Complex multi-agent systems with multiple integrations typically take 4–8 weeks. We deliver a working prototype for approval before the full build.
04
Which frameworks do you prefer for agentic AI development?
We use LangGraph for stateful agent orchestration, CrewAI for multi-agent collaboration, and AutoGen for research and code-generation agents. Framework choice depends on your use case.
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Location
Remote team serving US, UK, Europe & Australia
Reply Time
Within 24 hours
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