LLMOps
LLM Observability Is the New APM
If your application monitoring strategy stops at uptime and latency, you're flying blind — and your AI budget is quietly on fire.
Cost Katana
Cost Katana Team
March 10, 2026
7 min
Text-to-Agent Builder — now live
Say what you want.
Build what you need.From plain English to profitable AI agents — automatically.
Describe your agent in one sentence. CostKatana generates the pipeline, wires the nodes, optimises every token, and shows you exactly what it costs — live.
40–75%Token reduction via Cortex
100+Agent templates ready to deploy
<10msOptimisation overhead
400+Models across all providers
Cost Katana Is For You If...
Quickly see if our AI cost optimization platform matches your needs
- You're building or scaling AI-powered applications and need cost control
- You use multiple AI providers (OpenAI, Anthropic, Google, etc.) and want a unified view
- You want visibility into AI spend—which models, projects, and calls cost you the most
- You're looking to optimize prompt efficiency and reduce token usage
- You need real-time cost tracking and predictive analytics to avoid budget overruns
- You want to avoid vendor lock-in with a provider-independent architecture
- You need project-level budget tracking and cost allocation for teams
- You're concerned about prompt injection, data exfiltration, or runaway API costs
If several of these resonate, Cost Katana can help you slash AI costs by 40–75% while maintaining quality.
Act I · The problem
AI shipped everywhere.
Governed by nobody.
In the last 18 months, nearly every product team shipped an AI feature. Support bots. Code review. Sales emails. Onboarding flows. Fast, functional — completely ungoverned.
- →Most teams built AI like any third-party API — a quick
npm installand a weekend. No monitoring. No cost model. No quality gates. - !LLMs don't fail loudly. They fail quietly. No exceptions. No alerts. Wrong outputs reach production — you find out from a user complaint or an unexpected invoice.
- $Token costs fell 99% in two years. Bills didn't. Volume, waste, and ungoverned growth are the real driver — and nobody is watching.
- ↻Hallucinations trigger retries. Retries double your spend. Model drift silently bloats every prompt — and nobody tells you it happened.
The infrastructure to govern, observe, and optimise LLM costs doesn't exist for most teams. That's the gap CostKatana fills — starting the moment you describe your first agent.
Act II · Where tokens go
42% of every token
you pay for does nothing.
CategoryShare of spend%
Useful output
58%
Model drift waste
16%
Retry overhead
13%
Hallucination re-gen
9%
Prompt injection / illicit
4%
CostKatana's Cortex Optimizer targets every wasted category. It compresses prompts without quality loss, catches hallucinations before they trigger retries, and routes to the cheapest capable model. Average savings: 40–75% fewer tokens, applied automatically to every call.
Act III · The solution
You describe it.
CostKatana builds it.
Type what you want your agent to do — in plain English — and watch a complete, optimised, governed pipeline appear in seconds. No YAML. No schemas. No boilerplate.
CostKatana — Text to Agent Builder
Try an example
"Monitor new GitHub PRs, summarise each with Claude, post to Slack with a cost estimate, and flag any run over $0.05."
Generating pipeline…
01GitHub Trigger — PR.opened / PR.updatedTRIGGER
02Claude Sonnet 4.5 — PR SummariserLLM
03Cortex Optimizer — prompt compressionOPTIMIZE
04Cost Gate — flag if run > $0.05BUDGET
05Slack Notifier — post summary + cost tagOUTPUT
Estimated cost/run: $0.003Cortex saving: 61%Models used: 1Deploy ready:
Act IV · The lifecycle
Every step, governed.From first prompt to first profit.
CostKatana isn't just a builder. It's a complete AI agent operating system — tracking, optimising, and proving ROI at every step of your agent's life.
Build
Describe. Generate. Deploy.
Type what you need in plain English. The Text-to-Agent Builder constructs a complete multi-step pipeline — triggers, LLM steps, logic branches, output nodes — all wired automatically. No YAML. No JSON schemas. No boilerplate.
What gets generatedTrigger nodes · LLM steps with model selection · Cortex optimization injections · Conditional logic · Output channels · Budget caps
Optimize
Cortex compresses every token automatically.
Every LLM call passes through Cortex — CostKatana's 3-stage LISP-based meta-optimizer. It encodes your prompt, processes it, decodes a compressed version that preserves full semantic meaning. Result: 40–75% fewer tokens, same output quality.
Cortex pipelineEncoder → Core Processor (Claude Opus 4.1) → Decoder → compressed prompt → your provider
Route
Smart Gateway picks the best model for each call.
Not every call needs GPT-4. The Smart Gateway routes by capability, cost, and speed — automatically. If your preferred provider goes down, failover is instant. Provider lock-in becomes provider-agnostic flexibility.
Routing logic400+ models · capability-based routing · cost vs quality tradeoffs · automatic failover · semantic caching
Guard
GALLM catches hallucinations before users do.
GALLM runs a second model in parallel against every output. It attempts to disprove the response. If it can't: pass. If it can: flagged, logged, regenerated. This is the only hallucination guard that actively fights back.
GALLM mechanismPrimary LLM output → Adversarial model attempts disproof → Confidence score → Pass or flag → Regenerate if needed
Observe
Know exactly what every agent call costs and earns.
The Observability dashboard shows cost per call, per agent, per feature, and per project — live. Predictive analytics flags budget overruns before they happen. Weekly AI-enhanced digests tell you what changed and why.
What you seeCost per request · per-project breakdown · model usage heat map · hallucination rate · savings vs baseline · ROI per agent
Secure
Keys stay in the vault. PII stays out of LLMs.
The Key Vault holds all provider API keys encrypted at rest. PII redaction strips sensitive data before it reaches any LLM. Prompt injection defence blocks hijack attempts. Sandbox execution isolates every agent run.
Security layersEncrypted key vault · PII redaction · injection defence · sandbox execution · per-request budget caps · full audit logs
Act V · The cost paradox
Prices fell 99%.
Bills didn't.
GPT-4 family · input pricing per 1M tokens (USD)
$30GPT-4
2023
$10GPT-4
Turbo
$5GPT-4o
2024
$1.254o mini
$0.154.1 nano
↓ Token cost fell ~99.5% in 2 years. Most teams' LLM bills are still rising — volume, waste, and ungoverned growth are the real drivers. CostKatana governs all three.
- ↑As prices fall, teams ship more AI features — volume grows faster than per-token cost falls. The bill grows anyway.
- ?Without observability, there's no way to know which features are profitable and which are costing you money to give away for free.
- →CostKatana changes the question from "what did we spend?" to "what did we earn per dollar of AI spend?"
Act VI · Who uses CostKatana
One platform.
Every team.
Startups
Extend runway by eliminating wasted token spend. Know exactly which AI features are worth keeping before they eat your budget.
Enterprises
Govern AI usage across teams, projects, and providers. SOC 2 Type II, GDPR, RBAC, SSO — enterprise-ready from day one.
Developers
Five minutes from npm install cost-katana to full observability. Works with your existing stack — no architecture changes required.
Agencies
Track client AI usage separately. Show clients exactly what they're spending. Bill accurately. Prove ROI with data, not estimates.
Researchers
Maximise compute budgets with intelligent model routing. Batch processing and semantic caching eliminate redundant calls.
Any team shipping AI
If you're calling an LLM API without CostKatana, you're flying blind. Join the teams that know.
From the blog
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January 18, 2026
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Talk to Us
Have questions? We'd love to hear from you. Fill out the form below and we'll get back to you shortly.
Help us qualify your needs
Cost Katana is ideal for teams spending $1K+/month on AI across multiple providers. Answer the questions below so we can tailor our response and connect you with the right resources.
Plans & calculator
Pricing that scales with you
Start free, then pay for what you use—including token overages at $5 per 1M on paid plans. Compare plans, AI experimentation (model comparison & what-if), and model pricing on the full page.
View pricing & calculatorFrequently Asked Questions
Everything you need to know about Cost Katana and AI cost optimization
Cost Katana is an AI cost optimization platform that helps you reduce AI costs by up to 75% through intelligent features like Cortex optimization, semantic caching, model routing, and comprehensive monitoring. It provides real-time visibility into your AI spending across 300+ models from 12+ providers including OpenAI, Anthropic, Google, AWS Bedrock, and more.
Cost Katana typically delivers 40-75% cost savings through Cortex optimization and 70-80% additional savings through semantic caching. Our customers report average total savings of 60-85% on their AI infrastructure costs. The exact savings depend on your usage patterns, model selection, and optimization features enabled.
Getting started is simple: 1) Sign up for a free account at app.costkatana.com, 2) Install our SDK (npm install cost-katana), 3) Replace your existing AI provider calls with Cost Katana's unified API, 4) Configure your desired optimization settings. You can be up and running in under 10 minutes with immediate cost savings.
Cost Katana supports 300+ AI models across 12+ providers including OpenAI (GPT-4, GPT-3.5), Anthropic (Claude), Google (Gemini, PaLM), AWS Bedrock, xAI (Grok), DeepSeek, Mistral, Cohere, Meta (Llama), Azure OpenAI, HuggingFace, and Ollama. We continuously add new models and providers based on customer demand.
Cortex is our meta-language that converts natural language prompts into a more efficient, structured format. This reduces token usage by 40-75% while maintaining or improving output quality. Cortex uses semantic compression, redundancy elimination, and intelligent prompt engineering to minimize costs without sacrificing performance.
Semantic caching intelligently identifies similar requests and serves cached responses instead of making new API calls. Unlike traditional caching, it understands semantic similarity - so "summarize this document" and "create a summary of this text" would match. This can reduce costs by 70-80% for repeated or similar queries.
Yes, Cost Katana is built with enterprise-grade security. We offer Zero-Trust governance, multi-factor authentication (MFA), comprehensive audit logs, secure key vault management. Your data never leaves your control.
Cost Katana offers flexible pricing: Free tier with 10,000 requests/month, Startup plan at $49/month for growing teams, Pro plan at $199/month for scale, and Enterprise plans with custom pricing. All plans include core optimization features, with advanced features like custom models and dedicated support in higher tiers.
Integration typically takes 10-30 minutes for basic setup. Our SDK is designed as a drop-in replacement for existing AI provider SDKs. For complex enterprise deployments with custom requirements, implementation can take 1-3 days with our support team's assistance.
Cost Katana provides comprehensive monitoring including real-time cost tracking, performance metrics, model usage analytics, 65+ webhook events, OpenTelemetry observability, custom dashboards, alerts, and detailed reporting. You get full visibility into your AI infrastructure performance and costs.
Our intelligent routing automatically selects the most cost-effective model for each request based on complexity, required quality, latency requirements, and cost constraints. It can route simple queries to cheaper models while using premium models only when necessary, optimizing the cost-performance ratio.
Enterprise features include dedicated support, custom model fine-tuning, on-premises deployment, advanced governance controls, custom SLAs, priority feature requests, dedicated account management, and white-label options. Contact our enterprise team for a customized solution.
Still have questions?
Our team is here to help you optimize your AI costs
The verdict
Your AI is in production.Is it profitable?
- Group A hopes their AI is working. Discovers hallucinations from user complaints. Finds out about overruns from a surprise invoice.
- Group B knows. Cost per call. Quality per agent. ROI per feature. Bad outputs caught before users ever see them.
- CostKatana is the difference — five minutes, one SDK, zero code changes to your existing setup.
- "From 'we think it's working' to 'we can prove it.'"
costkatana.com · app.costkatana.com · npm install cost-katana · pip install cost-katana