Centralize multi-model cost, failover, and response routing with AI Smart Router

Put model selection, failure fallback, cost monitoring, and usage controls in one routing layer without locking business logic to a single provider.

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Application requestApply rules and budgetSelect model and fallbackRecord cost and result

Pricing

Pricing models

This solution is available as a one-time implementation project or a monthly SaaS module subscription. All amounts are before tax and are reference starting prices; the final quote depends on scope and usage. Before signing, we provide the service agreement with a review period of at least 5 days.

Implementation project · one time

NT$ 150,000 and up

Fixed quote by phase and scope, provided after discovery.

Monthly SaaS subscription

NT$ 3,000 and up/month

Tiered by module and usage; maintenance and advisory hours are available separately.

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Overview

Key points before implementation

Each solution can be implemented independently or combined with other Sainso modules into a complete enterprise AI platform.

Estimated build cycle

First MVP in 4-8 weeks

1 week for routing rule inventory, 1-2 weeks for architecture and API specs, 2-4 weeks for routing logic, and 1-2 weeks for monitoring and load testing. Some phases overlap, so the total is shorter than the sum of the phases. Paid discovery before the build (2–4 weeks) is not included.

Best fit

Internal AI platforms

Shared AI platforms across departments that need centralized permissions, billing, and model governance.

Features

Core capabilities

Every module maps to a clear business action, so the implementation does not become a one-time demo.

Intelligent routing

Select the best model by task complexity, latency target, reliability, and cost.

Automatic failover

Fallback when upstream APIs return 5xx errors, rate limits, or high latency.

Cost dashboard

Track usage and cost by project, user, and model, with alerts or downgrade rules.

Prompt cache integration

Combine provider cache strategies with duplicate prompt detection to reduce token spend.

Best Fit

Ideal use cases

These scenarios usually show value fastest and make acceptance criteria easier to define.

Internal tools

Internal AI tools

Centralize model access and reporting for multi-department AI usage.

SaaS teams

SaaS vendors

Stabilize customer-facing AI features and keep unit economics visible.

Agent builders

AI agent teams

Decouple model selection from business logic so providers can be swapped quickly.

Implementation

Implementation flow

Sainso moves in validated phases: clarify data and workflows first, then build the MVP and production rollout.

Discovery

Clarify goals, data sources, user roles, constraints, and success metrics.

Architecture

Define APIs, data models, permissions, cloud architecture, and operations model.

MVP build

Deliver the most critical workflow first so users can test and provide feedback.

Launch and operate

Deploy, monitor, optimize costs, and keep tuning models and workflows.

Tech Stack

Technology tags

The actual architecture is adjusted by security, data volume, integration complexity, and your existing environment.

Node.js Redis OpenRouter / OpenAI / Anthropic / Google Prometheus Grafana

Interested in AI Smart Router?

Tell us your industry, current system status, and budget range. We will reply within 2 business days and arrange a free 30-minute consultation with initial feasibility advice.

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