★ Featured
Agent Memory in 2026: Mem0 vs Zep vs Letta vs LangMem
Architecture deep-dive of Mem0, Zep/Graphiti, Letta, and LangMem - what each optimises for, when to pick which, and which benchmark claims to ignore.
AI-First Engineering Consultancy
We Build
AI Systems That
Ship to Production
CogniFlow Labs designs and engineers production-grade agentic AI, cloud-native platforms, and enterprise AEM experiences - for companies that need working AI, not just a proof of concept.
13+
Years Enterprise Engineering
12+
AI Agents Shipped
40+
Production Systems
85%
Average AI query resolution rate - no human in the loop
2M+
Monthly users served across AEM platforms delivered
60%
Avg. response time improvement post cloud migration
100%
Projects shipped to production - zero abandoned PoCs
Our Mission
Great AI is 10% model - and 90% engineering
Most AI projects fail not because the models are bad, but because the engineering around them is weak. No observability. No fallback logic. No production-grade infrastructure. CogniFlow Labs exists to close that gap.
Founded by Maidul Haque - Software Architect with 13+ years shipping production Java systems, enterprise AEM platforms, and cloud-native microservices - we bring the same engineering rigour to AI that we apply to every other layer of the stack.
Whether you need an autonomous agent, a RAG pipeline, an AEM platform with AI personalisation, or a cloud migration - every system we deliver is built to run reliably under real-world conditions, not just in a sandbox.
Production AI, never just PoCs
13+ yrs enterprise engineering
AI-native architecture design
MCP & Agentic AI specialist
AEM & Adobe Platform expert
Full-stack: Java + React + Cloud
Services
What You Get - Exactly
Every engagement has a clear scope, defined deliverables, and a production outcome. No vague retainers. No surprise scope creep.
🏆 Flagship Service
4–8 weeks
Agentic AI & LLM Systems
"A working autonomous agent - deployed, monitored, and ready to operate unsupervised."
I design and deliver production-grade agentic systems - from single-task LLM pipelines to complex multi-agent orchestrations with memory, tool use, and human-in-the-loop checkpoints. Every system ships with observability, cost controls, and fallback logic built in.
What you receive
- Multi-agent system with defined tools, memory & handoffs
- RAG pipeline tuned to your domain data and retrieval patterns
- LLM integration with cost controls, latency monitoring & fallbacks
- MCP server for structured, repeatable tool orchestration
- Full deployment on your cloud - AWS, Azure, or GCP
Best for: Enterprises automating complex workflows that currently require human judgment
Architecture
2–4 weeks
AI-Native Architecture
"A blueprint that treats AI as a first-class citizen - not something bolted on later."
Most architectures fail AI because they weren't designed for it. I design systems from the ground up where AI workloads, data flows, and model boundaries are considered at every layer - before a line of code is written.
What you receive
- Architecture design document with full component diagrams
- Architecture Decision Records (ADRs) for every key choice
- Data flow diagrams showing AI integration & boundaries
- Technology selection rationale - LLM, vector DB, orchestration
- Phased implementation roadmap with clear milestones
Best for: Teams about to build an AI product and need to start on solid ground
Infrastructure
3–6 weeks
AI Infrastructure & Cloud
"The cloud foundation your AI needs to run reliably - not just in demos."
I build and manage the infrastructure that keeps AI systems online, observable, and cost-efficient in production - from Kubernetes clusters optimised for LLM workloads to CI/CD pipelines with automated model evaluation gates.
What you receive
- Containerised AI services on Docker & Kubernetes
- LLM cost, latency & error monitoring dashboards
- CI/CD pipeline with model evaluation & regression gates
- Auto-scaling configuration for variable AI workloads
- Infrastructure as Code (Terraform) - fully reproducible
Best for: Teams whose AI prototypes keep breaking in production
Development
6–12 weeks
AI-Powered Full-Stack Apps
"A complete application with AI embedded at the core - not added as a feature afterwards."
I build end-to-end web applications using Java/Spring Boot backends and React/Next.js frontends, where AI is woven into the product logic from day one - not bolted on as a chatbot after the fact.
What you receive
- Production-ready Java Spring Boot API with AI endpoints
- React or Next.js frontend with AI features in the UX layer
- REST & GraphQL APIs with full OpenAPI documentation
- Automated test suite - unit, integration, and E2E
- CI/CD pipeline and cloud deployment with monitoring
Best for: Startups and enterprises building a new AI-powered product from scratch
Adobe / AEM
6–16 weeks
AI-Enhanced Digital Experiences
"Enterprise AEM platforms where AI doesn't just support the experience - it shapes it."
I deliver enterprise AEM platforms enhanced with AI personalisation - intelligent content decisions via Adobe Target, real-time audience segmentation via AEP, and headless architectures capable of serving AI-generated content at scale.
What you receive
- AEM Sites or AEM as a Cloud Service implementation
- Custom components, templates & editorial workflows
- Adobe Target integration with AI-driven A/B and personalisation
- AEP audience segmentation connected to real-time decisions
- Headless AEM / Content Fragments for omnichannel delivery
Best for: Enterprises looking to upgrade AEM or add AI personalisation to existing platforms
Consulting
1–2 weeks
AI Strategy & Consulting
"An AI roadmap grounded in engineering reality - not vendor hype or industry buzzwords."
I cut through the noise to give you an honest, technically grounded assessment of where AI can create real value in your business, what it'll actually take to build, and what the risks are.
What you receive
- AI readiness assessment of your current tech stack
- Prioritised AI use-case map with build/buy/partner decisions
- Architecture proposal for your top 2–3 use cases
- Quarterly implementation roadmap with measurable KPIs
- Ongoing technical advisory (weekly or monthly retainer)
Best for: Leaders who need a credible AI strategy before committing engineering budget
Technology
The Stack Behind the Work
Battle-tested technologies chosen for production reliability - not because they were trending on Hacker News.
GenAI & Agentic AI - Core Expertise
Claude (Anthropic)
OpenAI GPT-5.5
LangChain / LangGraph
Model Context Protocol (MCP)
RAG Pipelines
Vector DBs - Pinecone / PGVector
Mem0 / LangMem / Zep
Agentic Workflow Orchestration
Semantic Caching
Backend & Enterprise
Java 17 / 21
Spring Boot
Spring Cloud
Node.js
REST / GraphQL
PostgreSQL
Redis
MongoDB
Apache Kafka
Cloud & DevOps
AWS (Lambda, ECS, S3, RDS, Bedrock)
Microsoft Azure
Google Cloud Platform
Docker
Kubernetes
Terraform
GitHub Actions
GitLab CI
Frontend
Next.js
React
TypeScript
JavaScript (ES2024)
Tailwind CSS
Angular
Adobe Experience Stack
AEM 6.5 / AEM as a Cloud Service
Adobe Experience Platform (AEP)
Adobe Target
Adobe Analytics
Headless AEM / Content Fragments
Sling / OSGi
Our Work
Systems Built, Results Delivered
These aren't demos. Every project below is a production system with real users and measurable outcomes.
🤖
AI CORE
Agentic AI System
Autonomous Customer Support Agent
Built a production multi-agent system with LangGraph + Claude API - full tool use, conversation memory, CRM integration, and human escalation logic. Zero prompt engineering shortcuts.
✦ 85% query resolution - no human in the loop
🏗️
AI INFRA
AI-Native Architecture
E-Commerce Platform - AI-First Cloud Migration
Redesigned a monolithic platform into AI-ready microservices on AWS - event-driven architecture, semantic search layer, and AI recommendation engine integrated from day one.
✦ 60% faster response times, 35% lower infra cost
🎯
AI + AEM
AI-Enhanced AEM Platform
Enterprise Digital Experience Portal with AI Personalisation
Architected a global AEM Cloud platform for a Fortune 500 retailer - AI-driven personalisation via Adobe Target, AEP audience segmentation, serving 2M+ monthly users across 12 markets.
✦ 2M+ monthly users, 12 international markets
📊
AI POWERED
AI-Powered Application
Real-Time AI Analytics Dashboard
Full-stack dashboard processing 500K+ events/day, with an LLM layer that generates natural-language summaries and anomaly explanations alongside the live charts.
✦ 500K+ events/day, sub-second updates
⚙️
AI Infrastructure
ML-Aware CI/CD & Zero-Downtime Deployment Platform
Kubernetes-based deployment pipeline with automated model evaluation gates - deployments blocked if new model version underperforms baseline. Blue-green strategy, full rollback in under 2 minutes.
✦ Deploy time: 45 min → 8 min, zero failed releases
🏦
AI STRATEGY
AI Strategy & Architecture
Fintech Payments Platform - AI Fraud & Risk Layer
Led architecture from legacy monolith to event-driven microservices - PCI-DSS compliant, with a new AI-powered fraud detection layer integrated at the transaction processing stage.
✦ 99.99% uptime SLA, PCI-DSS compliant
How We Work
From Brief to Production
A structured process built around one goal: shipping working AI - on time, on budget, with full transparency.
AI Discovery
We map your AI goals, data landscape, technical constraints, and success metrics - before committing to any solution or stack.
Architecture First
You receive a full architecture proposal, ADRs, and phased roadmap before development starts. No surprises mid-build.
Build & Iterate
Agile delivery in 2-week sprints - weekly demos, clear progress tracking, and a staging environment from sprint one.
Ship & Monitor
Production deployment with observability dashboards, runbooks, and 30-day post-launch support. Your team owns it from day one.
Engagement Models
How We Engage
Three clear engagement models depending on what you need. Every project starts with a free 30-minute discovery call.
Show prices in:
Indicative starting prices — every engagement is scoped to your specific problem and context. Get in touch and we'll send a detailed quote within 48 hours.
Focused Engagement
Sharp insight. Fast turnaround.
A targeted, time-boxed engagement to unblock a decision, validate an approach, or diagnose a problem. Minimum overhead, maximum clarity.
Starting from
₹65,000
Fixed-fee engagement
Typical duration: 1–2 weeks
What's included
- AI readiness assessment of your tech stack
- Architecture review & written recommendations
- Proof-of-concept scoping & feasibility analysis
- Technical advisory sessions (up to 4 hrs)
- ADR documentation for key decisions
- Written summary with prioritised action plan
Ideal for: Teams validating an AI idea, needing a second opinion, or trying to get unstuck on an architecture decision before committing to a build.
Get a Quote →✦ MOST POPULAR
Project Engagement
End-to-end delivery. Production-ready.
A fully scoped project engagement delivering a production system — from architecture through development, testing, deployment, and handover.
Starting from
₹3,00,000
Scoped per project · up to ₹20,00,000
Typical duration: 4–12 weeks
What's included
- Full architecture design & ADR documentation
- End-to-end implementation of your chosen service
- Staging environment from sprint one
- Automated test suite (unit, integration, E2E)
- Production deployment with monitoring & alerting
- Runbooks, handover docs, & 30-day post-launch support
- Weekly progress demos — no black boxes
Ideal for: Startups and enterprises building a new AI system, full-stack application, cloud platform, or AEM implementation.
Get a Quote →Strategic Partnership
Sustained engineering capacity.
An ongoing retainer for businesses that need dedicated AI engineering expertise — without the overhead of a full-time hire. Scales with your needs month to month.
Starting from
₹1,50,000
Per month · 3-month minimum
Minimum: 3-month commitment
What's included
- Dedicated engineering capacity (days/week agreed upfront)
- Priority response — under 4 hours during business hours
- Monthly strategy & architecture governance sessions
- Multiple concurrent workstreams supported
- CTO-as-a-Service available for leadership needs
- Quarterly AI roadmap reviews with updated recommendations
Ideal for: Scale-ups and enterprises that need sustained AI engineering leadership without committing to a senior in-house hire.
Get a Quote →Writing & Thinking
Inside the Work
Technical deep-dives on the systems, patterns, and decisions behind real AI and enterprise engineering.
AEM as an MCP Server: AI-Driven Operations for Enterprise Content
How I built a self-hosted MCP server for AEM operations - 15 tools, dual-path AEMaaCS/6.5 support, query safety, and a production path for enterprise teams.
★ Featured
GitNexus Deep Dive: The Knowledge Graph for AI Coding Agents
How GitNexus gives AI coding agents real codebase awareness - indexing pipeline, Leiden clustering, hybrid BM25+RRF search, and when to use it over RAG.
★ Featured
Semantic Caching in Production: Beyond the Hype
How I built a 4-layer semantic cache for e-commerce search - two-zone thresholds, adaptive TTL, Kafka invalidation, and six production pitfalls nobody documents.
★ Featured
AEM 6.5: Are You Planning Your Next Move Before Support Ends?
AEM 6.5 support ends February 2027. An honest breakdown of your two paths - AEM LTS or AEMaaCS - and why the organisations that wait are the ones I see scrambling.
Let's Talk
Ready to Build Something Real?
Tell us about your AI challenge. We'll come back within 24 hours with an honest assessment of how we can help - and whether we're the right fit.
Start the conversation
Whether you need a production AI agent, a cloud migration, an AEM platform overhaul, or a straight-talking second opinion on your architecture - we're here to help you build the right thing, the right way.
Tell us about your project
Message received!
We'll review your project and respond within 24 hours.
We'll review your project and respond within 24 hours.