Carraggon CarraZero
Specialized models for every production AI system.
CarraZero trains enterprise-grade rerankers, embeddings and custom models — light-weight, blazing fast, and accurate where generalist models aren't.
Accuracy
Up, on your data
P90 latency
~500ms → ~80ms
Cost per query
Fraction of generalist
Deployment
Cloud, VPC or on-prem
The limit on enterprise AI isn't the frontier model. It's whether the retrieval layer surfaces the right thing, fast enough, on your own data. CarraZero fixes that layer.
The stack
The CarraZero stack.
Four specialized layers you can adopt one at a time — each one drops into the pipeline you already run.
01
CarraRank — rerankers
State-of-the-art cross-encoder reranking. Drop it in front of any retrieval layer and get dramatically more accurate results with one line of code.
02
CarraEmbed — embeddings
Domain-tuned embedding models for enterprise corpora: contracts, tickets, claims, listings, SOPs and code. Better recall where general embeddings blur.
03
CarraTune — custom models
Small, focused models fine-tuned on your workflow data — classification, extraction, routing and scoring — trained, evaluated and versioned by us.
04
CarraServe — inference
Purpose-built serving stack. Open-weight models on optimized runtimes for the lowest latency at enterprise concurrency.
Why specialized
Small models, trained narrow, win.
Accuracy up
CarraZero's specialized models replace generalist alternatives with state-of-the-art accuracy on your domain. Better models in, better answers out.
Latency down
Small, focused models run faster than generalist alternatives — fast enough for real-time applications and agents at scale.
Noise out
Perfect relevance instead of noisy results. Ranking is trained against your judgements, not a public leaderboard.
Ownership
Open-weight foundations, your data, your evals. Deploy in your VPC and keep the weights when the contract ends.
Benchmarks
Outperforms generalist models on retrieval.
Indicative NDCG@10 on a mixed enterprise retrieval benchmark. We re-run these on your corpus before you commit to anything.
0.6382
0.7080
0.7266
0.7563
0.7625
Generalist A
Generalist B
Generalist C
CarraRank-1
CarraRank-2
Before
~500 ms
After
~80 ms
Retrieval API + reranker
129.7 ms
Use cases
Where CarraZero pays for itself.
Enterprise search
Millions of documents, ranked the way your experts would rank them.
RAG & agents
Retrieval quality is the ceiling on agent quality. CarraZero raises it.
Support deflection
Route, match and answer from your real ticket history.
Claims & underwriting
Extraction and scoring models tuned to your policy language.
Listings & matching
Rank inventory against intent, not keywords.
Code & knowledge
Internal repos, runbooks and wikis surfaced with precision.
Cost
Better specialized models cut cost across the stack.
Fewer tokens wasted on irrelevant context — and CarraZero is cheaper at every layer: embedding, ranking, inference and the generation call downstream.
Context tokens
Fewer passages, tighter prompts
Model spend
Small models, lower unit cost
Downstream LLM
Shorter prompts, cheaper calls
Infrastructure companies and devtools — voice AI, agent memory, enterprise search — rely on specialized retrieval for accurate results across hundreds of thousands of daily queries.
Deploy
Ship models that work.
Integrate CarraZero models in minutes. Production-ready, latency-optimized, available everywhere — one API, or through your existing cloud.
Partner providers
Access every model through a single latency-optimized API, or deploy through our partner providers and keep inference inside your own account.
# Create an API key in the Carraggon console
from carrazero import CarraZero
client = CarraZero()
response = client.models.rerank(
model="carrarank-2",
query="Which vendor contracts renew in Q3?",
documents=docs,
top_n=10,
)Bring us your hardest retrieval problem.
We'll benchmark CarraZero against whatever you run today — on your data, in a week.
Schedule your intro call→