zkVerify is a purpose-built verification layer where apps, rollups, and protocols can submit zero-knowledge proofs, get them verified, and receive attestations that can be used across multiple destination chains.
They support major proof systems, and when you’re operating at “proof verification layer” scale, the data layer stops being a backend detail and becomes part of the product.
The Problem
zkVerify is designed to process massive verification throughput and issue attestations across chains - and that comes with brutal requirements:
- Real-time visibility into network activity (what’s happening now)
- Fast historical queries (what happened before, reliably and cheaply)
- Internal analytics + monitoring (so performance stays high even when activity spikes)
They needed to solve three concrete pains:
- Making on-chain verification data easily queryable
- Handling high-throughput indexing without latency headaches
- Tracking attestations across multiple destination chains
Why zkVerify Chose SQD
zkVerify is a Substrate-based L1. They stated that “given zkVerify runs on Substrate, SQD emerged as the natural choice within the ecosystem.”
But fitting the conversation wasn’t enough. The decision hinged on three critical factors:
1) Native Substrate support
zkVerify needed indexing infrastructure that genuinely comprehends Substrate chains. Native support meant building without wrestling the tooling from day one.
2) Custom schemas for domain-specific data
zkVerify’s data structure includes:
- proof verification events
- verifier pallet interactions
- cross-chain attestations
- proof-specific metadata
This proved decisive. The team noted that “the capacity to establish custom schemas for specialized data types proved essential” and that “SQD’s SDK permitted modeling domain-specific data in configurations that standard indexing solutions couldn’t accommodate.”
3) Throughput efficiency without expensive infra overhead
When processing proof-scale volume, inadequate indexing approaches force costly infrastructure decisions (archive nodes, constant tuning, endless RPC pressure).
zkVerify’s aim was straightforward: real-time access, efficient batch processing, and reliable performance under load.
SQD matched that operational reality.
Bonus: a developer-friendly GraphQL layer
Once indexed, teams still need to use the data across products, dashboards, and tooling. SQD’s GraphQL serving options integrated neatly into that workflow.
Integration
zkVerify adopted SQD early—before legacy data setups required unwinding—which enabled architecting the data layer around SQD’s capabilities from inception.
The main challenge wasn’t implementation. It centered on correctly modeling zkVerify’s specialized structures:
- proof verification events
- cross-chain attestation flows
- verifier pallet interactions
zkVerify constructed:
- custom processors for verifier pallets (decoding and indexing proof-specific metadata)
- custom handlers for cross-chain attestation events
Importantly, they highlighted the SQD team’s contribution in shaping schemas for performance optimization: “SQD’s team delivered exceptional guidance on designing schemas to maximize query efficiency.”
Results
1) Real-time data access without expensive archive nodes
The team reported “SQD enabled real-time data access without maintaining costly archive node infrastructure ourselves.”
An operational simplification win.
2) Batch processing that holds up under proof-scale throughput
They noted that “batch processing manages proof verification volume efficiently, even during peak-activity periods.”
This reflects experience navigating actual high-activity periods without performance degradation.
3) Service quality stays high because visibility stays high
SQD powers zkVerify’s internal monitoring and KPI tracking, providing clear sightlines into network activity and verification throughput—helping them detect issues quickly and maintain reliable service levels.
What This Unlocks for zkVerify
Once the data layer becomes reliable and queryable, infrastructure evolves from “minimum viable monitoring” into genuine product surface:
- verifier pallet usage analytics (actual usage patterns and adoption)
- cross-chain attestation tracking dashboards (attestations remain observable across chains)
- ecosystem health monitoring tools (activity, throughput, and pattern visibility)
Since zkVerify plans expanding attestation support, modular data pipelines matter: “We can incorporate new data sources and chain integrations without dismantling existing indexing systems.”
SQD Support
zkVerify’s feedback proved unambiguous: responsive, technically skilled, and rapid-moving.
The team stated that “SQD’s team demonstrated exceptional responsiveness and technical expertise” while recognizing “quick resolution turnarounds on technical queries enabled development velocity and prevented pre-launch blockers.”
Conclusion: when verification is the product, the data layer can’t lag
zkVerify builds a modular proof verification layer designed to make verification more accessible and universal.
Supporting diverse proof systems only matters if the system remains observable, debuggable, and scalable as throughput expands.
They selected SQD because they required:
- native Substrate indexing without tooling friction
- custom schemas for domain-specific verification and attestation data
- throughput efficiency during high-activity periods
- monitoring-grade reliability, not “demo-grade” indexing
- a partner team enabling faster shipping
Summarizing their choice: “SQD delivers on performance, flexibility, and developer experience.”
If you’re building anything involving high-volume, domain-specific data that conventional indexers struggle to model—SQD is purpose-built for that. Contact Konstantin, Partnership Lead, via k.kalinin@sqd.ai or Telegram @xyz_konstantin.