Your Problem, Understood

Before proposing solutions, we need to verify we understand what you're actually trying to solve. Here's our interpretation of your business requirements.

"We've studied your technical specification in depth. We understand what you're trying to achieve, and we believe there's a faster, lower-risk path to get there."

Reading between the lines of your specification, here are the five core business problems we believe you're solving:

01

Contributor Trust

"Don't lose my voice"

What You Said

Coq machine-checked proofs for CRT_Uniqueness, RNS_NoOverflow, GETA_Invariant, and formal verification of determinism composition.

What We Heard

Contributors need cryptographic proof their input is included in the final mix. They must be able to verify their contribution wasn't lost.

02

Dispute Resolution

"Stop disputes"

What You Said

Same inputs must produce identical outputs. Determinism guaranteed via Q31.32 fixed-point arithmetic and RNS residue systems.

What We Heard

Platform must prove outputs are legitimate and reproducible. Any third party should be able to replay and verify results.

03

Cost Efficiency

"Stop burning money"

What You Said

O(1) incremental aggregation via GETA algorithm with RNS arithmetic. Heavy-path execution limited to <0.5% of events.

What We Heard

Can't reprocess everything on every update. Adding voice N must be O(1), not O(N). Processing costs must stay manageable at scale.

04

Audit Trail

"Prove provenance"

What You Said

TON blockchain anchoring with Merkle roots. HSM-signed receipts. Optional Arweave/IPFS perma-pointers for artifact storage.

What We Heard

Verifiable chain from contribution to final artifact. Immutable proof that can't be disputed or altered after the fact.

05

Scale Path

"Handle billions eventually"

What You Said

MVP target of 5M voices. DiskANN + Product Quantization for billion-scale search. Sharding strategies for time/geography.

What We Heard

Architecture must support billions—but not necessarily on Day 1. Prove the approach works, then scale.

Key Insight

We agree 100% with these goals.

Our disagreement is purely about implementation—not what you need, but how to get there.

Shared Goals

Outcomes We Both Want

These business outcomes remain unchanged in our counter-proposal.

Outcome #1

Deterministic Outputs

Same inputs always produce identical outputs. Verifiable, reproducible, bit-for-bit.

Outcome #2

O(1) Aggregation

Adding voice N takes constant time regardless of N. No full recompute required.

Outcome #3

Blockchain Anchoring

Immutable proof on TON. Merkle roots, signed receipts, verifiable provenance.

Outcome #4

Billion-Scale Search

Find-my-voice in p99 <100ms. Architecture proven for 1B+ embeddings.

Outcome #5

High-Quality Audio

MOS ≥3.5 on official mixes. Professional-grade denoising and synthesis.

Outcome #6

Fast Previews

Preview generation in p95 ≤60s. Contributors see results quickly.

The Difference

Same Outcomes, Different Mechanisms

Here's where our proposal diverges: not on what to achieve, but how.

Requirement
Your Mechanism
Our Mechanism
Determinism Proof
Coq Formal Proofs
Test Suite (N=10)
Numeric Stability
RNS + Q31.32
Welford's Algorithm
Audio Enhancement
3-Model Ensemble
DeepFilterNet3
MVP Validation
5M Voices
100K + 10M PoC

The core insight: You don't need a research project to solve your problem. You need battle-tested engineering with rigorous testing discipline.

Did we understand correctly?

Does this accurately reflect your core business requirements? If you have any concerns or need to clarify any points, we would be happy to schedule a call with our technical team to ensure full alignment.

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The Counter-Proposal
Interactive side-by-side comparison engine