DS
Deepak Suhag
Expert Advanced AI Service
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AI Agent Development

Autonomous AI agents that get work done end-to-end

We build production-grade AI agents — single-purpose task agents, multi-agent orchestration systems, and tool-using LLM pipelines that autonomously complete complex multi-step workflows.

10+Years building AI
50+Projects delivered
98%Client satisfaction
72hAvg. first response
Why work with us

What you get

Every engagement is designed around clear business outcomes — not just technical deliverables.

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End-to-End Automation

Agents that research, decide, act, and report — without human intervention for routine tasks.

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Tool Use

Agents that browse the web, query databases, write files, send emails, and call APIs.

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Planning & Memory

Long-horizon planning with persistent memory so agents don't repeat themselves.

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Observability

Every agent step is logged, traceable, and auditable — critical for enterprise compliance.

Why Deepak Suhag

Built Different. Delivered Different.

We are not a big-4 consulting firm with layers of juniors — we are senior practitioners who have built and shipped real systems at scale.

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10+ Years of Production AI

We have shipped AI systems used by millions — not slide decks, but deployed, monitored production code.

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Results-Driven, Not Hours-Driven

We measure success by your business outcomes: reduced costs, more revenue, faster operations.

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Deep Technical Depth

Senior engineers across ML, backend, cloud, and data — no generalists who dabble, only specialists who ship.

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Radical Transparency

We tell you when AI is not the right answer. Our goal is your success — not our revenue.

Our Approach

How we work

A battle-tested process refined across 50+ projects — fast, transparent, and built for production from day one.

01

Workflow Analysis

Decompose the target workflow into discrete steps; identify where autonomy is safe.

02

Tool Inventory

Identify and build all tools (APIs, browser, file system) the agent needs to complete the task.

03

Agent Architecture

Design the agent loop — ReAct, plan-and-execute, or multi-agent collaboration pattern.

04

Guardrails

Define what agents can and cannot do; add human approval gates for irreversible actions.

05

Monitor & Refine

Trace every agent run, measure success rates, and improve the prompt/tool loop iteratively.

Technologies We Use

Our tech stack

We pick the best tool for the job — not the one we happen to know. Here is what powers our AI Agent Development engagements.

Agent Frameworks

🕸️LangGraph🤖AutoGen👥CrewAI🟢OpenAI Assistants🟣Anthropic Tool Use

Tool Use & Memory

🌐Browser Use🎭Playwright🌲Pinecone🐘pgvector🔴Redis

Observability

🔍Langfuse🔗LangSmith📊Arize🔭OpenTelemetry

Deployment

🚀FastAPI🐳Docker☸️Kubernetes☁️AWS Lambda
What we build

Typical projects

From rapid MVPs to enterprise-grade systems — here are the kinds of projects we tackle.

Research & summarisation agentsLead qualification agentsCode review agentsData extraction agentsCustomer onboarding automation
Our Engagement Models

Choose how we work together

No one-size-fits-all pricing. We adapt to your project type, team size, and budget.

Most Popular
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Fixed-Price Project

Clearly scoped deliverables, timeline, and price. Zero surprises — you know exactly what you are paying for.

  • Detailed scope document
  • Fixed-cost proposal
  • Milestone-based payments
  • 30-day post-launch support

Ideal for: Defined projects with clear requirements

Best for Growth
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Monthly Retainer

Dedicated hours each month for ongoing development, optimisation, and strategic AI guidance.

  • Dedicated senior engineer hours
  • Weekly strategy calls
  • Priority support SLA
  • Monthly roadmap reviews

Ideal for: Growing SaaS and product companies

Enterprise
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Team Augmentation

Dedicated engineers embedded in your team — same timezone, same tools, same Slack.

  • Full-time dedicated engineers
  • Direct Slack/Teams access
  • Embedded sprint participation
  • Knowledge transfer sessions

Ideal for: Enterprises scaling their tech teams

FAQ

Common questions

Still have questions? Ask us directly →

How reliable are AI agents in production?

Reliability depends on task complexity and guardrails. We design for graceful failure and human escalation on uncertainty.

What's the difference between an AI agent and a chatbot?

A chatbot responds. An agent acts — it can autonomously take steps, use tools, and complete tasks without being prompted each step.

How do you prevent agents from taking wrong actions?

Tool permissions, confidence thresholds, human-in-the-loop gates, and immutable audit logs.

Ready to start?

Let's build something
extraordinary together.

Book a free 30-minute discovery call. No sales pitch — just an honest conversation about your challenge and how we can help.

Ask Deepak's AIHow can I help scale your growth?