AI Services

Build AI leverage into your business. We deliver production-grade AI agents, RAG systems, and automated workflows aligned to outcomes.

Why CloudArc for AI

AI from people who ship code.

The reasons clients pick us, in their own words. Each one is something most AI firms will swear they do — and most don't.

BUILDERS01

Builders first.

Most AI consultants have never shipped a product. We ship them weekly. We know where AI breaks in production because we've debugged it ourselves — that's a different kind of operational intelligence than a demo.

PRODUCTION-GRADE02

Production-grade, not proof-of-concept.

We build AI systems that handle real traffic, real edge cases, and real users. Evaluation frameworks, monitoring, and safety guardrails are built in from day one.

FIX INCLUDED03

Fix included, not just findings.

Strategies that end with "here's what you should do" are useless. Every engagement ends with implemented, tested, and deployed AI systems — not just a roadmap.

COST-AWARE04

Cost-aware by default.

AI costs can spiral fast. We optimize for cost per inference, use model distillation where it makes sense, and build monitoring that catches cost anomalies before your CFO does.

Coverage

The full AI surface.

Not a checklist. The specific AI services we deliver on every engagement, from a single strategy session to an ongoing retainer.

A01

AI strategy & consulting.

Use case discovery, data readiness assessment, ROI modeling, and strategic roadmap development to align AI initiatives with business outcomes.

A02

Custom AI agent development.

Production-grade AI agents with RAG systems, agentic workflows, tool integrations, and comprehensive evaluation frameworks.

A04

AI workflow automation.

Intelligent automations across sales, support, and operations with built-in governance, monitoring, and human-in-the-loop capabilities.

A05

RAG & retrieval systems.

Retrieval-augmented generation for knowledge bases, customer support, and document intelligence with vector databases and semantic search.

A06

AI safety & governance.

Evaluation frameworks, red-teaming, bias detection, and safety guardrails for production AI systems.

Who This Is For

Three situations, one team.

Most clients fall into one of three shapes. Fixed-price or retainer, senior engineers only — no account-manager layer between you and the person doing the work.

EXPLORING AIDISCOVERY

Teams exploring AI for the first time

  • Not sure where AI fits in your product
  • Need use case discovery and ROI modeling
  • Data readiness assessment required
  • Want a strategic roadmap before building
Get an AI strategy
BUILDING AIPRODUCTION

Teams building AI-powered products

  • Need production-grade AI agents
  • RAG systems for knowledge retrieval
  • Evaluation frameworks and safety guardrails
Build AI agents
SCALING AIOPTIMIZATION

Teams scaling existing AI systems

  • AI costs growing faster than value
  • Need model optimization and distillation
  • Governance and monitoring gaps
  • Human-in-the-loop workflows needed
Optimize your AI

Process

From discovery to deployed AI.

A typical AI engagement, end-to-end. The optimize-and-scale phase is optional — plenty of clients just want the build.

01

Discover & assess

We map your data landscape, identify high-ROI use cases, and assess readiness. Fixed quote before any work starts.

02

Prototype & validate

Rapid prototyping with real data. We validate feasibility and ROI before committing to full production build.

03

Build & evaluate

Production-grade development with comprehensive evaluation frameworks, safety guardrails, and monitoring built in.

04

Deploy & optimize

Gradual rollout with A/B testing, cost optimization, and continuous improvement based on real-world performance.

Stack

AI tools we reach for first.

Picked by problem, not by resume. We're happy to swap into your stack — but on a green-field AI build, this is the default.

OpenAIAnthropicLangChainLangGraphVector DBs (Pinecone, Weaviate)RAG & RetrievalLLM Fine-tuningPythonNode.jsAWS BedrockGCP Vertex AI

Related Work

You might also need.

FAQ

Straight answers.

Do you build custom AI models, or use existing ones?
Both. We start with existing foundation models (OpenAI, Anthropic, etc.) and fine-tune or distill when the use case demands it. Custom model training is reserved for cases where it genuinely adds value.
How do you handle AI safety and bias?
Safety is built in from the start: evaluation frameworks, red-teaming, bias detection, and safety guardrails are part of every AI system we deliver. We don't ship AI that we wouldn't trust ourselves.
What's the typical cost of an AI project?
Fixed quote after the discovery phase, when scope is genuinely known. A typical AI agent build runs 4-8 weeks. Larger scopes get honest timelines, not squeezed ones.
Can you work with our existing data and infrastructure?
Yes — we adopt your stack and improve from inside it. We're happy to work with your existing data pipelines, cloud provider, and ML infrastructure.
How do you measure AI project success?
Every AI project starts with measurable outcomes: accuracy targets, latency requirements, cost per inference, and business metrics. We build evaluation frameworks that track these from day one.
Do you offer ongoing AI operations?
Yes — many clients continue with a retainer for model monitoring, retraining, cost optimization, and safety reviews. AI systems need ongoing care, not just deployment.

Senior Engineers

Build AI that actually works in production.

Free 30-minute call with a senior engineer. We'll tell you honestly whether you need an AI strategy, a custom agent, or nothing at all — and exactly what it would cover.