Early Access Now Open for SOMA (SN114)’s Copilot Compression Layer

Early access for SOMA (SN114) is live, delivering one of the sharper token savings offers in the coding agent market. The current release covers GitHub Copilot as the coding surface and DeepSeek V4 Pro as the underlying model.

SOMA’s compression layer intercepts every prompt between them, cutting token volume without touching response quality. More models are coming through the early access window based on feedback from active users.

What Early Access Delivers

The launch product covers one clean workflow, giving early testers concrete conditions to measure whether compression works on real coding tasks.

1. GitHub Copilot integration works as the first supported coding surface: Existing users plug the SOMA key into their setup without changing anything else in the workflow.

2. DeepSeek V4 Pro serves as the underlying model behind compressed prompts: The layer cuts token volume flowing to the model without changing response quality Copilot expects.

3. Installation runs through one bash command with the API key: Keys generate once and hash on the server, so copy before leaving the page since no second display exists.

4. Prepaid credits handle billing with 100 credits per $1 of upstream usage: Payment accepts card or $TAO directly, with requests returning a 402 status once your balance hits zero until top-up.

Real coding workloads become the benchmark for whether promised savings hold up under production conditions.

Try SOMA (SN114) on a Real Coding Workload Today

Anyone paying Copilot bills scaling faster than their engineering output has a specific reason to test SOMA against a live workload right now. Also, raw feedback on what works, what breaks, and where the compression pipeline is needed for improvement across the next wave of models.

Getting started takes one bash command against the API key generated on SOMA after signup. Early access opens the door, and genuine feedback on real tasks shapes what the product looks like next quarter.

➛ Try SOMA (SN114) Here.