AI That Works. Data That Delivers.

AI isn't the goal.
Business outcomes are.

AgentFaktory helps organizations design, build, and deploy practical AI, data, and analytics solutions that solve real business problems — without the hype, complexity, or endless experimentation.

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About Us
Agentic Workflow AutomationKnowledge Graph IntelligenceReal-time Data PipelinesLLM-powered CopilotsComputer Vision MonitoringDocument IntelligencePredictive AnalyticsEnterprise IntegrationsMCP ConnectivityCloud Data ModernisationRAG ApplicationsAI Governance & ObservabilityAgentic Workflow AutomationKnowledge Graph IntelligenceReal-time Data PipelinesLLM-powered CopilotsComputer Vision MonitoringDocument IntelligencePredictive AnalyticsEnterprise IntegrationsMCP ConnectivityCloud Data ModernisationRAG ApplicationsAI Governance & Observability
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Snowflake Select Services Partner

AgentFaktory is a Snowflake Select Services Partner.

We bring Snowflake-backed delivery capability into data engineering, Cortex AI, governance, and modernisation programmes, while still designing around the full data stack a client already runs.

Snowflake capability Data platformsCloud stacks

The honest truth

Most AI projects
fail before
they ship.

Not because the models were wrong. Because the architecture was, the data wasn't ready, or the brief was never properly defined.

We prevent that.

Try it now

Describe your business problem.

The AgentFaktory assistant will recommend the most relevant service, solution, or industry capability — and guide you directly to the right page.

This assistant is itself a live example of the kind of intelligent systems AgentFaktory builds — a governed AI assistant connected to real business knowledge, with proactive navigation and lead intelligence built in.

Start with a question — or try one of these:

What we build

End-to-end capability.
Nothing outsourced.

Services are how we help. Solutions are where we start faster. We combine advisory, engineering, AI, analytics, and integrations with reusable accelerators for common enterprise problems.

AI & Intelligent Systems

Agents, copilots, RAG, computer vision — production AI that sits on solid data. Built to ship, not to demo.

Consulting & Advisory

Strategy, architecture, and technology roadmaps — before a single line of code is written.

Data Engineering

Snowflake, Databricks, dbt — the data foundation that everything else runs on.

90% production-focused engagements

Analytics & BI

Dashboards and KPIs that business users actually trust and use daily.

Knowledge Graphs

Surface hidden relationships across enterprise data with Neo4j, Neptune, or EidoGraph.

Enterprise Integrations

SAP, Salesforce, ServiceNow — a governed connectivity layer everything shares.

12+ enterprise industries and business domains addressed
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Reusable AI & Data Accelerators

Explore our demo engines

Live examples of the AI and data systems we build. Each is a reusable foundation we customise around your data, systems, workflows, and governance requirements.

✓ We are not starting from zero.
✓ We have reusable foundations already built.
✓ We customise them around your data, systems, workflows, and governance requirements.
Live Demo

AI Business Analyst

Ask business questions in plain language. Get answers grounded in your actual data.

What it showsMulti-hop traversal across a knowledge graph — decomposing a business question into entities, relationships, and metrics to produce a cited answer.
Business problemAnalysts spend hours on ad-hoc data requests. Executives wait days for answers that should take seconds.
Production connects toSnowflake, Databricks, PostgreSQL, BI tools, Excel, ERP, CRM. Answers include source citations and drill-down evidence.
Explore demo
Live Demo

Document Intelligence

Extract, classify, and route information from unstructured enterprise documents.

What it showsHow a PDF is classified, fields extracted with confidence scoring, flagged for human review, and routed into a workflow.
Business problemManual document handling is slow, error-prone, and unscalable across contracts, invoices, compliance filings, and claims.
Production connects toSharePoint, email inboxes, ERP, CRM, approval workflows, and data warehouses. Processes thousands of documents per hour.
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Live Demo

Agentic Workflow Automation

AI agents that plan, execute, and coordinate multi-step business workflows.

What it showsMultiple agents collaborating — one plans, one retrieves data, one validates, one executes — with human approval gates.
Business problemComplex workflows that break RPA — variable inputs, conditional logic, multi-system dependencies — are left manual.
Production connects toAny enterprise system via MCP or API. Full observability, audit trails, and human-in-the-loop checkpoints.
Explore demo
Live Demo

MCP Integration Platform

Governed, reusable integration between AI assistants and enterprise systems.

What it showsAn AI assistant executing a tool call against an enterprise system — with policy enforcement, approval gate, and audit log.
Business problemAI assistants either have no access to real business data or are given dangerous unrestricted access with no oversight.
Production connects toSAP, Salesforce, ServiceNow, Oracle, Dynamics, custom APIs. Granular permissions, approval flows, and full audit trails.
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Live Demo

Conversational AI

AI assistants that understand intent, access live data, and resolve issues end-to-end.

What it showsA multi-turn conversation where the agent understands context, calls live systems, and resolves a request without human escalation.
Business problemMost chatbots are scripted FAQ systems. They break on anything unexpected and cannot access real customer data.
Production connects toWhatsApp, voice, web chat, CRM, ERP, ticketing systems. Resolves 70%+ of contacts without human involvement.
Explore demo
Live Demo

Computer Vision & Monitoring

AI-powered visual monitoring that detects anomalies, violations, and operational events.

What it showsReal-time detection of safety events, intrusions, or quality defects — grouped into prioritised incidents with evidence attached.
Business problemHuman operators cannot watch all camera feeds simultaneously. Events are missed, reviews happen too late, evidence is lost.
Production connects toCCTV infrastructure, SCADA, warehouse management systems. Monitors 100% of feeds, logs every event with visual evidence.
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Who builds this

Built by enterprise AI, data, and architecture practitioners.

AgentFaktory is built by senior practitioners with hands-on experience across enterprise data platforms, analytics, AI applications, system integration, and production delivery. We have worked inside the organisations we now help — which means we understand the constraints, the politics, and the gap between a demo and a working system.

We are not a strategy-only advisory firm. We are not a chatbot agency. We design, build, integrate, and deploy working systems — and we stay engaged until they are adopted.

Enterprise Data PlatformsAI Application EngineeringKnowledge Graph ArchitectureSystem Integration & MCPProduction Delivery

How we deliver

A process built for
production, not demos.

Every engagement follows the same seven-step discipline — because shortcuts are how AI projects fail.

01

Diagnose the business problem

Clarify the real operational, financial, or customer problem before choosing technology.

02

Assess data and systems

Review data quality, architecture, integrations, access patterns, and governance constraints.

03

Design the target architecture

Define the data, AI, integration, security, and user experience layers.

04

Select accelerators

Reuse relevant AgentFaktory engines where they fit — AI Business Analyst, Document Intelligence, MCP Integration — adapted to your data and workflows.

05

Build and integrate

Connect to enterprise systems, workflows, APIs, databases, and user interfaces.

06

Govern and test

Add access control, observability, human approvals, audit trails, and validation.

07

Deploy and measure

Move beyond POC into adoption, production usage, and measurable business outcomes.

Example work patterns

Patterns of work across industries.

Anonymised examples of the type of problems we have worked on and the systems involved.

Principles

What we do not do.

Knowing what not to do is as important as knowing what to build.

Build AI demos disconnected from real business systems or data.

Recommend LLMs before understanding the data, workflow, and governance model.

Treat access control, observability, and audit trails as afterthoughts.

Force a single platform when Snowflake, Databricks, Azure, AWS, GCP, or open-source tools may be better suited.

No demos. No generic pitches.

Tell us what you're
trying to solve.

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Dubai, UAE · [email protected]