We buildAI that ships

Q: How long does a typical AI agent project take?

Most MVPs ship in 4-8 weeks. Enterprise deployments with complex integrations typically take 3-6 months. We'll provide a detailed timeline during our discovery phase based on your specific requirements.

Q: Do you work with startups or only enterprises?

Both. Our modular approach scales from $10K proof-of-concept engagements to multi-year enterprise partnerships. We've helped early-stage startups build their first AI features and supported Fortune 500 companies modernize their infrastructure.

Q: What cloud platforms do you support?

We're cloud-agnostic but specialize in AWS, Azure, and GCP. We also work extensively with Databricks, Snowflake, and hybrid on-premise/cloud environments. Our team holds multiple AWS and Databricks certifications.

Q: How do you handle data security and compliance?

Security is built-in, not bolted on. We implement encryption at rest and in transit, audit logging, role-based access control, and governance patterns that meet SOC2, HIPAA, and GDPR requirements. Every project includes a security review.

Production-ready AI agents. Enterprise-grade cloud infrastructure. Measurable outcomes.

Start Your Project See Our Work

Certified By

AI AgentsThat Ship

Production-ready agentic workflows with observability, security, and measurable outcomes.

Multi-AgentOrchestration

Coordinate teams of specialized agents for complex workflows.

CloudEngineering

Scalable, secure infrastructure built for reliability.

DataPlatforms

Governed pipelines that turn data into insights.

WorkflowAutomation

Safe automation with human-in-the-loop controls.

Our Process

How We Work

A proven 4-phase methodology to deliver production-ready AI and cloud systems.

●

PHASE 01

Discovery & Strategic Alignment

We align on goals, constraints, and success metrics. You get a clear plan: what to build first, expected impact, and how we measure it.

Discovery workshop + problem framing

Opportunity map + ROI model

Risk, security, and data readiness review

PHASE 02

Agentic Architecture Design

We design the system architecture, data flows, and guardrails for safe automation then translate it into a build-ready backlog.

System architecture + integration plan

Model/tooling selection (model-agnostic)

Evaluation plan and acceptance criteria

PHASE 03

Deployment & Optimization

We build, integrate, and deploy to production with observability, testing, and operational readiness baked in from day one.

MVP build + integrations

Monitoring, tracing, and alerting

Performance tuning and reliability hardening

PHASE 04

Scale & Knowledge Transfer

We scale responsibly and hand over clean documentation and playbooks so your team can own and extend the system long-term.

Scale plan + cost optimization

Documentation, runbooks, and training

Ownership transfer and next-step roadmap

Our Tech Stack

Trusted Technologies

We use industry-leading platforms to deliver robust, scalable, and secure AI and cloud solutions.

Cloud Infrastructure

AI Ecosystem

What We Offer

Services

End-to-end AI and engineering to ship reliable systems.

Agentic AI FrameworksProduction-ready AI agents with guardrails

Multi-Agent OrchestrationCoordinate multiple agents reliably

LLM Fine-Tuning & RAGGrounded answers on your private data

Predictive ModelingForecasting and anomaly detection

Agentic AI Frameworks

Production-ready AI agents with guardrails

Design and ship AI agents that automate high-value workflows with strong controls, observability, and secure integrations.

Agent design + tool integrations (APIs, DBs, internal systems)
Evaluation harness + safety checks
Audit logs, tracing, and monitoring
Secure deployment patterns (IAM/VPC/KMS)

OUR WORK

Portfolio

Platforms we build, systems we modernize, and measurable outcomes we deliver.

FEATURED PLATFORM

ASK-INSIGHT

An agentic AI platform for enterprise workflows.

A platform blueprint we use to deliver production-grade agentic workflows: tool use, multi-agent orchestration, and retrieval (RAG) grounded in enterprise knowledge. Built with observability, security, and human-in-the-loop controls from day one.

Multi-Agent Orchestration

Deploy specialized agents that collaborate research, analysis, code generation, and execution in harmony

Tool Use & MCP Integration

Agents with native tool calling APIs, databases, code execution, web browsing, and custom MCP servers

RAG & Knowledge Graphs

Advanced retrieval with vector search, knowledge graphs, and hybrid RAG for accurate, grounded responses

Autonomous Workflows

Self-improving agents with memory, planning, reflection, and human-in-the-loop guardrails

AVAILABLE CHANNELS

Slack

Web Chat

Voice

Request Demo

Analyze our customer churn patterns from the last 6 months and predict the revenue impact for Q1 2025

Multi-Agent OrchestrationComplete

Connected to AWS S3 data lake0.8s

Retrieved customer activity logs (1.2M records)2.4s

Applied ML model: churn_prediction_v34.1s

Generated revenue impact forecast1.2s

Customer Churn Rate Trend

6-month historical + 2-month forecast

ActualPredicted

At-Risk by Segment

Enterprise847

40%

Mid-Market1,203

27%

SMB797

10%

Churn Drivers

Pricing Concerns42%

Feature Gaps31%

Support Satisfaction18%

Competitor Switch9%

8.4%Churn Rate+68% vs baseline

2,847At-RiskEnterprise: 847

$1.2MQ1 ImpactIf no action

Critical Alert: Churn rate increased 87% over baseline. Top drivers: pricing (42%), feature gaps (31%). Recommend immediate enterprise intervention.

Case Studies

Real outcomes,
not demos

CLOUD NATIVE

Automated Reporting

Architecting a petabyte-scale serverless data lake and distribution ecosystem handling millions of daily records and 10k+ personalized reports.

View Case Study

SECURITY & CLOUD

Secure File Transfer

Enterprise-grade serverless media ingest workflow with banking-level security, handling thousands of secure transfers and automated processing jobs.

View Case Study

AGENTIC AI

Image Generation

Cutting-edge Generative AI platform utilizing RAG and SageMaker to deliver hyper-personalized visual assets with sub-second inference latency.

View Case Study

CLOUD INFRASTRUCTURE

UN-FAO

Scaled global application infrastructure for the United Nations, automating deployment across 40+ regional clusters with AWS and Terraform.

View Case Study

FAQ

Common Questions

Everything you need to know about working with us

What makes Cloftech different from other AI consultancies?

We focus on production-ready systems, not demos. Every solution ships with observability, security, and measurable KPIs from day one. Our team has delivered 50+ projects with 99.9% uptime across enterprise and startup clients.

How long does a typical AI agent project take?

Do you work with startups or only enterprises?

What cloud platforms do you support?

How do you handle data security and compliance?

Trusted By

Companies building
the future

From startups to enterprises, we help teams ship production-ready AI systems securely and reliably.

50+Projects Delivered

99.9%Uptime Achieved

We buildAI that ships

AI AgentsThat Ship

Multi-AgentOrchestration

CloudEngineering

DataPlatforms

WorkflowAutomation

How We Work

Discovery & Strategic Alignment

Agentic Architecture Design

Deployment & Optimization

Scale & Knowledge Transfer

Trusted Technologies

Services

Agentic AI Frameworks

Portfolio

ASK-INSIGHT

Multi-Agent Orchestration

Tool Use & MCP Integration

RAG & Knowledge Graphs

Autonomous Workflows

Customer Churn Rate Trend

At-Risk by Segment

Churn Drivers

Real outcomes,not demos

Automated Reporting

Secure File Transfer

Image Generation

UN-FAO

Common Questions

Companies buildingthe future

Real outcomes,
not demos

Companies building
the future