Service

Artificial Intelligence

From custom models to production-ready AI systems — we deliver intelligence that scales with your business and generates measurable ROI.

Predictive AnalyticsNLPComputer VisionAgentic AILLMsRAGAI development companycustom AI solutions

60%

Avg. reduction in manual processing time

8–12wk

Typical pilot-to-production timeline

99.9%

Uptime SLA on hosted AI services

Overview

What is Artificial Intelligence

Artificial intelligence is no longer a future trend — it is a competitive necessity. At Arcifacts, we build custom AI solutions that integrate seamlessly into your products and operations: from large language model integrations and retrieval-augmented generation (RAG) pipelines, to computer vision and autonomous agentic workflows. Every solution we build is engineered for reliability, observability, and scale.

Built for enterprises and ambitious product teams that need real AI capabilities — not just demos. Whether you're adding a conversational layer to your SaaS, automating document-heavy workflows, or building an AI-native product from scratch, we have the engineering depth to deliver.

What you get

Faster time-to-market for AI-powered features

Models that maintain accuracy in production with continuous monitoring

Clear roadmap from proof-of-concept to enterprise deployment

Measurable cost reduction through intelligent automation

Artificial Intelligence — overview

Deliverables

What we deliver

Every engagement is scoped to your exact needs — here's the full catalogue of deliverables we can provide.

🧠

Custom LLM & GPT Integrations

Production-ready integrations with OpenAI, Anthropic Claude, and open-source models — with RAG pipelines, prompt engineering, and guardrails.

⚙️

Agentic AI & Workflow Automation

Multi-step AI agents that reason, plan, and execute tasks across tools and APIs — using LangChain, LangGraph, and CrewAI frameworks.

💬

NLP & Conversational AI

Chatbots, smart search, document Q&A, and intent-based routing systems trained on your business data.

👁️

Computer Vision Systems

Image classification, object detection, OCR, and document understanding pipelines for real-world visual data.

📊

ML Model Development

Custom predictive models for churn, demand, fraud, recommendations, and more — trained, validated, and deployed.

🔄

MLOps & Model Monitoring

End-to-end infrastructure for model training, versioning, deployment, drift detection, and automated retraining.

— Process

Our process

01

Discovery & Strategy

We align on goals, scope, and success metrics through structured workshops and stakeholder interviews.

02

Design & Architecture

Blueprint and UX aligned with your brand, technical requirements, and long-term scalability needs.

03

Development & Iteration

Agile sprints with regular demos, feedback loops, and transparent progress tracking.

04

QA & Optimization

Rigorous testing across devices and edge cases with performance tuning before launch.

05

Launch & Handoff

Smooth deployment, full documentation, and knowledge transfer so your team owns the outcome.

06

Support & Evolution

Ongoing support, monitoring, and iterative improvements to keep pace with your growth.

AI Stack

Technologies & tools we use

Work

Work highlights

A selection of outcomes we've delivered for clients across industries.

40%Downtime Reduced

Predictive Maintenance Platform

Built an ML pipeline for a manufacturing client to predict industrial equipment failures before they occur, integrating IoT sensor data with a real-time inference API.

40% reduction in unplanned downtime, saving $2M+ annually.

60%Faster Processing

Legal Document Intelligence

Deployed an NLP system for a legal tech firm to automatically extract, classify, and summarise clauses from contracts — replacing hours of manual review.

60% faster document processing across 10,000+ monthly contracts.

Why us

We build outcomes,
not just deliverables.

01

Production-first ML engineering — we build for real scale, not just demos

02

Strong data and MLOps practices ensuring models stay accurate over time

03

Transparent model governance with explainability and audit trails

04

Deep expertise across the full AI stack: data, training, inference, and monitoring

We architect every AI solution for enterprise-grade scale and compliance from day one — so you can go from a 100-user pilot to a million-user deployment without rebuilding.

FAQ

Frequently asked questions

Still have questions? Reach out and we'll answer directly.

Pilots and proof-of-concepts typically run 6–10 weeks. Full production systems, including data pipelines and MLOps infrastructure, usually take 3–5 months depending on data readiness and scope complexity.

Get started

Ready to build with AI?

Tell us your goals and we'll outline a clear, honest path from idea to production — with timelines, costs, and expected outcomes.

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No long-term lock-in
Response within 24h
Fixed-price or T&M