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Service 03

LLM Strategy & Optimization

Most businesses use AI naively. We architect your entire AI stack — prompt engineering, model routing, RAG pipelines, cost optimization — so you get better outputs at a fraction of the cost.

70%
Average cost reduction
Output quality improvement
48hrs
Audit turnaround time
LLM STACK OPTIMIZATION
❌ BEFORE
ModelGPT-4 (always)
PromptCasual, no system
RAGNone — hallucinating
Cost/query$0.12
✓ AFTER
ModelRouted intelligently
PromptEngineered system
RAGConnected knowledge base
Cost/query$0.003 (↓ 97%)
70% cost reduction · 3× output quality

The Problem

Most companies burn $50k+/yr on AI tools and get mediocre results.

The problem isn't the AI — it's how it's being used. Weak prompts, wrong model selection, no retrieval layer, no governance. We've audited hundreds of AI stacks and the pattern is always the same: massive spend, poor outputs, frustrated teams. We fix this at the root.

Teams using GPT-4 where GPT-4o-mini would be 10× cheaper and just as good

Prompts written casually instead of engineered systematically

No RAG means hallucinations and dangerously outdated information

No governance means AI used inconsistently — or not at all

Our Approach

How we work.

01
Day 1–3

LLM Stack Audit

We audit every AI tool in your stack: what you're spending, what models you're using, and what outputs you're getting.

02
Week 1

Waste Identification

We identify exactly where budget is being burned — overpriced models, inefficient prompts, redundant tools.

03
Week 2

Architecture Design

We design your optimized AI stack: right models per task, prompt systems, RAG setup, and governance framework.

04
Week 3–4

Implementation

We build and deploy the optimized system: prompt libraries, retrieval pipelines, model routing, and monitoring.

05
Ongoing

Iteration & Training

As models and use cases evolve, we keep your stack current. New use cases built each month on retainer.

What You Get

Everything included.

01

Full LLM Stack Audit

Complete inventory of every AI tool in use, total spend, model selection rationale, and output quality assessment.

02

Prompt Engineering System

Professionally engineered system prompts for every use case — tested, versioned, and documented for your team.

03

Model Routing Strategy

The right model for the right task. Reduce cost 40–70% through intelligent model selection without sacrificing quality.

04

RAG Pipeline Setup

Retrieval-Augmented Generation connected to your knowledge base — eliminating hallucinations and enabling private data use.

05

Cost Optimization Report

Detailed breakdown of pre/post costs with projected annual savings. Typically pays for itself within the first 2 months.

06

AI Governance Framework

Usage policies, approval workflows, and monitoring systems so AI is used consistently and safely across your organization.

Real Results

70%
Average cost reduction achieved
Output quality improvement
2mo
Average payback period

We were spending $23k/month on AI tools and getting mediocre outputs. After their audit, we spend $7k and get dramatically better results.

DR
David R.
CTO, Enterprise SaaS

Pricing

Transparent. No surprises.

Audit

$2,500

Know exactly what to fix

Full LLM stack audit
Waste identification report
Optimization roadmap
Model selection recommendations
48-hour delivery
30-min strategy call
Get Started
Most Popular

Implement

$8,000

Audit + full implementation

Everything in Audit
Prompt engineering system
Model routing setup
RAG pipeline (1 knowledge base)
Cost monitoring dashboard
Team training session
Get Started

Retainer

$3,000/mo

Ongoing optimization & new use cases

Ongoing stack monitoring
New use cases built monthly
Prompt version management
Model cost optimization
Monthly performance report
Priority Slack support
Get Started

FAQ

Common questions.

Still have questions? We'd love to talk through your specific situation.

Ask us anything

OpenAI (GPT-4o, GPT-4o-mini), Anthropic (Claude 3.5 Sonnet, Haiku), Google (Gemini 1.5 Pro, Flash), Mistral, Llama, and custom fine-tuned models. We are completely model-agnostic.

Usually not. The audit identifies which existing tools to keep, optimize, or replace. Most clients keep 60–70% of what they have, just configured better.

RAG (Retrieval-Augmented Generation) lets your AI access your private documents, knowledge base, or database to give accurate, up-to-date answers. Most businesses benefit significantly.

Our audits find 40–70% cost savings for most clients, primarily through model routing and prompt optimization. The $2,500 audit typically identifies $20k+ in annual savings.

That's exactly who we work with most. We build the system, document everything, and train your team. You don't need to know how it works under the hood — you just need to see the results.

Ready to start?

Let's talk about
your LLM goals.

30-minute discovery call. We'll audit your current situation and map out exactly where we can move the needle.

Book a Call hello@citeara.com