AI Agent Café
// services · 01 / 05

AI services that ship to production,not to a slide deck.

AI Agent Café is an AI consulting, development, and training company helping startups and SMBs design, build, and deploy agentic AI systems — from first roadmap to running agents.

Book a discovery call →Explore agentic services
20
service lines
5.0
bootcamp rating
2×
time zones
48h
response time
// section_01

Strategy & Advisory

Most AI initiatives fail before a line of code is written — because the use case, the tooling, or the expectations were wrong. We help you get all three right first.

01

AI Strategy & Roadmap Development

Adopting AI without a plan leads to scattered experiments and stalled momentum. We build a phased roadmap mapped to your data, team, budget, and goals.

// deliverables
  • →Prioritized opportunities scored on value, feasibility, and time-to-ship
  • →6–18 month phased roadmap with milestones and expected ROI
  • →Data readiness assessment — what you have, what's missing
  • →Model & infrastructure recommendations (API vs. open-source, cloud vs. on-prem)
  • →A concrete “start here” first project designed to prove value in weeks
Ideal forFounders & leaders who need a de-risked path from intent to implementation.
02

AI Use-Case Discovery & Prioritization Workshops

A structured, hands-on workshop with your team to surface where AI can genuinely move the needle. We map workflows, identify friction, and score every candidate on feasibility, impact, and effort.

FormatHalf-day or full-day, on-site (Delhi NCR) or remote.
OutputRanked use-case backlog your team can act on immediately.
03

AI Vendor & Tool Selection

The AI tooling landscape changes monthly, and vendor marketing rarely matches production reality. We run independent, hands-on evaluations of models, frameworks, and platforms against your workload — with real benchmarks and PoC code.

Answered with evidenceBuild vs. buy vs. partner — not feature-comparison spreadsheets.
// section_02 · flagship

Agentic AI & Automation

Our core expertise: AI agents that do real work. We design and build autonomous and semi-autonomous agents that plan, use tools, remember context, and complete multi-step workflows — reliably, observably, and in production.

04flagship

Custom AI Agent Development

Generic chatbots answer questions. AI agents complete work. We build purpose-built agents that research prospects, reconcile invoices, draft reports, monitor markets, or run operational pipelines end-to-end.

// deliverables
  • →Reliable tool use — real systems (CRM, DBs, email, APIs) with retries and error handling
  • →Memory that persists — short-term, semantic, and episodic memory architectures
  • →Guardrails built in — scoped permissions and input/output validation
  • →Full observability — every decision, tool call, and token traced
StackLangGraph · Claude / GPT / open-source · FastAPI · Docker · PostgreSQL · AWS
05flagship

Multi-Agent System Design & Orchestration

A single agent asked to research, analyze, write, and publish will do all four poorly. Multi-agent systems give each agent one job and orchestrate them into a team.

// deliverables
  • →Supervisor — a coordinator routes work to specialists and assembles output
  • →Swarm — peer agents hand off control dynamically as tasks shift
  • →Hierarchical — teams of teams for large, complex operations
  • →Production plumbing — shared state, failure isolation, cost controls, per-agent eval
06flagship

Agentic Workflow Automation

Business processes branch, loop, wait for approvals, and fail halfway through. We automate entire workflows using stateful agent graphs on LangGraph and CrewAI.

// deliverables
  • →Durable execution — checkpoint state at every step; resume where it left off
  • →Conditional branching on data, agent decisions, or business rules
  • →Parallel fan-out with clean merges
  • →Long-running processes that span hours or days, pausing for approvals
07high growth

MCP Server Development & Integration

The Model Context Protocol is the emerging open standard for connecting AI agents to tools and data. One secure, reusable integration layer that works across every AI application.

// deliverables
  • →Custom MCP servers exposing internal systems as standardized tools
  • →Integrations with the growing ecosystem — Gmail, Notion, Slack, GitHub, and more
  • →Auth, scoped permissions, and audit logging
  • →Multi-framework compatibility — LangGraph, CrewAI, Claude, and any MCP client
08

Human-in-the-Loop (HITL) Agent Workflows

Full autonomy isn't always the goal — control is. Agents that pause for human approval on high-stakes actions: sending client emails, executing trades, publishing content, issuing refunds. Includes approval queues, notifications, editable outputs, and audit trails.

09

Voice Agents (Inbound / Outbound / IVR Replacement)

AI-powered calling agents that hold natural conversations — no more “press 1 for sales.” Inbound answers and routes with context; outbound qualifies leads and confirms appointments. Real-time STT/TTS, wired into your telephony and CRM.

10

Legacy RPA → Agentic AI Migration

Traditional RPA bots break on every UI change and can't handle exceptions. We migrate the right processes to agents that reason about the task, adapt to change, and handle edge cases — as a phased migration with parallel runs.

// section_03

Generative AI & LLM Solutions

From retrieval pipelines to production guardrails — the engineering layer that turns a powerful model into a dependable product.

11flagship

RAG System Development

LLMs don't know your business — RAG fixes that. We ground every answer in your documents, databases, and knowledge, reducing hallucinations without retraining models.

// deliverables
  • →Production RAG — ingestion, chunking, embeddings, hybrid search, reranking, citations
  • →Advanced patterns — Agentic RAG, Corrective RAG, Self-RAG, Graph RAG
  • →Retrieval quality engineering with proper evaluation datasets
  • →Vector infra — Pinecone, Qdrant, ChromaDB, or pgvector
12

Custom Chatbots & Conversational AI

Production chatbots for web, product, WhatsApp, or Slack — persistent memory, consistent brand voice, tightly grounded in your knowledge base. Escalation to humans, analytics, and multilingual support.

13

Enterprise Knowledge Base & AI Search

Company knowledge scattered across drives, wikis, tickets, and inboxes — unified into one AI-powered search layer. Plain-language questions, cited answers, respected access controls.

14

Document Intelligence & Structured Data Extraction

Turn invoices, contracts, resumes, and forms into clean structured data. OCR + LLM extraction with strict Pydantic schemas, business-rule validation, and review queues for low-confidence cases.

15critical

Agent Evaluation, Testing & Observability

The #1 reason AI projects stall after launch: nobody can tell if the system is getting better or worse. We ship evaluation and observability infrastructure with every build.

// deliverables
  • →Evaluation suites — curated datasets and automated scoring on every change
  • →Tracing — every prompt, tool call, decision, token, and cost (LangSmith / LangFuse)
  • →Production monitoring — quality drift, latency, error rates, and spend
  • →Regression protection before model or prompt updates reach users
16

LLM Guardrails, Safety & Cost Optimization

Block prompt injection, PII leakage, and off-policy outputs. Cost architecture — semantic caching, model routing, fallback chains — that can cut LLM bills by 40–70%.

// section_04

Industry Solutions

Domain-shaped AI, built by teams who understand the workflows.

17

AI for Customer Support

Three layers of AI: automatic ticket triage, end-to-end auto-resolution grounded in your help docs, and agent assist that drafts responses and surfaces knowledge in real time. Faster response, lower cost per ticket, humans on cases that matter.

18

AI for Finance & Trading

Built by practitioners who trade. Market analysis agents, real-time news sentiment engines, and algorithmic trading systems — from signal generation to auditable execution aligned with regulatory requirements (including SEBI's algo norms).

// section_05

Product & Enablement

Ship your AI product. Level up your team.

19flagship

AI Product Development — MVP to Scale

For founders building AI-native products: architecture, agent logic, backend APIs, deployment, and iteration. We've shipped our own AI products — and we build yours the same way.

// deliverables
  • →Weeks to MVP, not months — proven architecture patterns in front of real users fast
  • →Full stack — agent/LLM layer, FastAPI backend, vector + relational DBs, Docker on AWS
  • →Built to scale — the MVP grows into the production system; no throwaway prototype
  • →Your code, your IP — clean, documented handover with your team trained to own it
20flagship

Corporate AI Training & Agentic AI Bootcamps

The biggest bottleneck in AI adoption isn't technology — it's skills. Hands-on, code-first training that takes engineering teams from LLM basics to shipping production multi-agent systems.

// deliverables
  • →Agentic AI Bootcamp — flagship cohort program (rated 5.0, sold out): LangChain, LangGraph, CrewAI, RAG, MCP, deployment
  • →Corporate workshops — 1–5 day intensives on your use cases, on-site or remote
  • →Executive AI literacy sessions for leadership and boards
  • →Developer upskilling tracks converting Python developers into AI engineers
// how_we_work

Four steps from idea to running system.

01

Discover

A focused call to understand your workflow, data, and goals — and whether AI is genuinely the right answer.

02

Design

A concrete solution blueprint: architecture, model choices, cost estimates, and success metrics — before any commitment to build.

03

Build

Iterative development with weekly demos. You see working software every step — no black-box delivery at the end.

04

Deploy & Enable

Production deployment with monitoring and guardrails, plus training so your team can own, operate, and extend the system.

// why_ai_agent_café

Boutique by design.

Small team, senior operators, honest scopes. We turn down more work than we take on.

  • 01Production-first engineering — checkpointing, observability, guardrails, cost controls built in.
  • 02Current stack, always — LangGraph, CrewAI, MCP; systems updated as the ecosystem moves.
  • 03Founder-led delivery — you work with senior practitioners, not a rotating bench of juniors.
  • 04Knowledge transfer included — every engagement ends with your team owning what we built.
  • 05Right-sized for startups & SMBs — enterprise-grade engineering without the overhead.
// let's_ship

Got an agent that needs to ship?

We take on a small number of new engagements each quarter. Reach out with the rough shape of the problem and we'll get back within 48 hours.

Start a conversation →contact@aiagentcafe.com