[ MANIAC ]

high throughput
task specialized
background agents

Outperform Opus 4.6 on your niche domain tasks.
1/100 the cost of large frontier models, so your agents can run 24/7.

maniac — architecture
live
Client
Your Agents
Background tasks at scale
calls today
2,847,291
Maniac Engine
Router
Routes each request to optimal model variant
Models
Fine-tuned, distilled, compressed for your domain
Optimization Loop
traffic → curate → finetune → eval → promote → repeat
Opus 4.6 quality · 1% of the cost
>Opus 4.6
on-domain accuracy
1%
of the cost
<400ms
p50 latency
10M+
calls / day
Built & Backed by

Benchmarks

Cost per 1M input tokens on background agent workloads. Quality measured against Claude Opus 4.6 on domain-specific evaluation suites.

ProviderCost / 1M input tokensp50 LatencyQuality vs Opus
Claude Opus 4.6$15.002.1sbaseline
GPT-5.2$10.001.4s94.2%
GPT-4.1$2.00620ms87.1%
Maniac Optimized$0.10340ms99.1%

SMART ROUTING

Every request is routed to the optimal model variant. When an optimized model outperforms your flagship, routing switches seamlessly. Zero code changes.

AUTO OPTIMIZATION

Maniac runs continuous experiments on your production traffic—fine-tuning, distillation, compression—and auto-promotes winners.

CUSTOM EVALS

Define what "better" means for your domain. Plug in custom judges, human feedback, or task-specific metrics. We optimize against your real objective.

How it Works

Three steps. No AI team required. A few engineering hours to get started.

01

Point your agents at Maniac

Swap your API endpoint. Maniac exposes an OpenAI-compatible interface—your existing code, SDKs, and frameworks work unchanged.

pythonagent.py
from maniac import Maniac
 
client = Maniac()
 
container = client.containers.create(
label="extraction-agent",
initial_model="openai/gpt-5",
)
 
response = client.chat.completions.create(
container="extraction-agent",
messages=[{"role": "user", "content": prompt}],
)
02

We optimize automatically

Maniac captures production traffic, builds domain-specific training sets, and runs continuous experiments. Winners are promoted automatically.

pythonconfig.py
container.evals.add(
criteria="Extraction accuracy",
judge_model="openai/gpt-5",
threshold_samples=1000,
)
 
container.optimization.configure(
strategy="continuous",
methods=["finetune", "distill", "compress"],
auto_promote=True,
)
03

Ship frontier quality at 1% cost

Optimized models go live through seamless routing. Your agents get frontier-quality responses. Models only get better over time.

pythonoutput
# Nothing changes in your code.
# Maniac handles routing automatically.
 
# Before: $15.00 / 1M tokens
# After: $0.10 / 1M tokens
 
# Quality: >Frontier on-domain
# Latency: <400ms p50
# Uptime: 99.97%

Built for Scale

Background agents running millions of tasks need Opus-quality reasoning without the Opus-quality price tag.

DATA EXTRACTION

Millions of documents. Opus-quality parsing.

Extract structured data from PDFs, contracts, and invoices at massive scale. Background agents process documents around the clock—Maniac ensures every extraction is Opus-quality at a fraction of the cost.

100x
cost reduction vs direct Opus calls
PREDICTION & SCORING

Millions of predictions. Frontier accuracy.

Score leads, forecast demand, or predict churn at massive throughput. Task-specialized models outperform general-purpose frontier models on your specific prediction tasks—at a fraction of the cost.

10M+
predictions / day
CLASSIFICATION

High-volume labeling and routing.

Classify support tickets, moderate content, or triage alerts at 10M+ events per day. Maniac-optimized models match Opus accuracy on your specific taxonomy.

99.1%
accuracy vs Opus baseline

Limits

Real numbers from production deployments.

MetricObserved in ProdCurrent Limit
Max throughput (global)10M+ calls/dayUnlimited
Max throughput (per container)500K+ calls/day1M calls/day
Max concurrent requests50K+Unlimited
Optimization cycle time~4 hoursConfigurable
Model variants per container12+50
Quality match vs Opus 4.699.1%
p50 latency<400ms
p99 latency<1.2s
Max context window128K tokens128K tokens
Uptime SLA (Enterprise)99.97%99.9%

[ GET STARTED ]

Start shipping
in minutes

OpenAI-compatible API. No infrastructure changes. Start free, scale to millions of agent calls.

terminal
$ pip install maniac
$ maniac init --container my-extraction-agent   Container created: my-extraction-agent   Initial model: openai/gpt-5   Endpoint: https://api.maniac.ai/v1
$ maniac status  ┌─────────────────────────────────────────────┐   Container: my-extraction-agent                 Status:    ● active                              Model:     maniac-opt-v3 (promoted)          Quality:   99.1% vs opus 4.6                   Cost:      $0.75 / 1M tokens                 Calls:     2.4M today                       └─────────────────────────────────────────────┘