Vendor lock-in
Prices go up without notice, models get deprecated, usage policies change. Code tied to a single provider gets rewritten — or you pay whatever they ask.
Synapse routes each task to the right model — Claude, GPT, Gemini, Llama or a proprietary Bluey model. Simple questions go to cheap models. Heavy analysis goes to top models. You only pay for what makes sense.
Mid-market companies adopting AI through a single provider's API discover three pains within months: the bill explodes, operations get locked in, and when the model goes down, the company stops with it. A multi-LLM router neutralizes all three risks at once.
Prices go up without notice, models get deprecated, usage policies change. Code tied to a single provider gets rewritten — or you pay whatever they ask.
Premium models cost 10-30× more than efficient ones. When every prompt hits the top model, the bill grows with no quality gain. Trivial tasks don't need expensive brains.
Provider downtime means squad down, support down, pipeline down. Without automatic failover to another model, your continuity depends on an SLA you don't control.
The Synapse router isn't a manual switch — it's a decision layer that classifies the task, compares it to agent policy and picks the right model. All before the prompt leaves your infrastructure.
The router reads the prompt and identifies: simple, medium or complex? Text, number, code, multimodal? Critical or routine? This sets the eligible model tier.
Each squad has its own rule. Finance squad never uses open-source models. Marketing squad can use Gemini for images. You define — the router obeys.
Within the eligible tier, the router picks for best cost-quality ratio in real time: current latency, provider queue, price per token, historical accuracy for the task type.
If the chosen model fails or stalls, the router redirects to the next in the queue without the user noticing. Operational continuity without depending on a single SLA.
You don't pick the model — you pick the outcome. But if you want to know who's behind the scenes, here is the platform's current catalog. New models ship continuously, without changing your squads' code.
Opus, Sonnet and Haiku family
Deep reasoning, long-context analysis and reliable structured generation. Opus for critical analysis, Haiku for high-volume, low-cost workflows.
GPT-5 family and mini variants
Strong at natural language generation, code interpretation and multimodal. Excellent general baseline for communication and productivity squads.
Pro and Flash family
Generous context window, great cost at scale and native visual processing. Ideal for ingesting large documents and visual tasks at volume.
Open-source for on-prem scenarios
Open model running on the customer's own infra — for cases where sensitive data cannot leave the network. The router treats Llama like any other provider.
Alternative efficient families
Aggressive pricing tier for classification, extraction and high-volume workflows. The router scales automatically when cost drives the decision.
In-house reranker and classifiers
Proprietary models trained by Bluey for the internal pipeline: RAG reranker, task classifier, PII detector. Components where Bluey controls accuracy end-to-end.
Serious multi-LLM isn't just "having APIs for multiple models" — it's architecture that decides, measures, fails over, audits and isolates per tenant. Here is how Synapse implements each piece.
Not a manual selector: each agent declares a policy and the router decides per call based on task type, criticality and each provider's current SLA.
Primary provider down? Router redirects to the secondary at the same quality tier — without the user noticing. Retry with backoff and controlled degradation when all providers degrade.
Every call logs model, tokens, latency and cost. Dashboard shows how much each squad consumes per day, week, month — and where you can optimize by switching tiers.
Equivalent questions don't need to hit the LLM twice. The cache identifies semantic similarity, returns the validated answer and saves tokens on repeating workflows.
Data tagged as sensitive never goes to an external provider — only on-prem Llama or Bluey models. Native PII detection blocks leaks before the call leaves the network.
Each customer has separate quota, keys and telemetry. No data enters model fine-tuning — Bluey or third-party. The Branches system applies isolation between units of the same group.
No Synapse AI decision goes directly to an external model. Squads, Your Base and Governance all flow through the router to guarantee cost, quality and compliance end-to-end.
Each squad declares its policy — the router resolves which model runs each workflow step. The squad doesn't know providers, it just knows the expected outcome.
RAG retrieves the right documents, the router picks the brain that interprets them. Heavy question goes to Opus, simple question goes to Haiku — context stays the same.
Every call logs the chosen model, reason, cost and outcome. Audit shows compliance which brain processed what — always traceable.