Summary: Most “slow” on-chain apps aren’t CPU-bound—they’re state- and data-bound. This playbook shows when to keep compute in Solidity, when to offload to L2/DA layers, and when to prove results with ZK so Enterprise teams hit SOC2-grade control, predictable budgets, and clear ROI.

Target audience: Enterprise (keywords: SOC 2, ISO 27001, procurement, ROI, SLAs)

Optimizing Heavy Computation On-Chain (or Moving it Off-Chain)

Pain — Your contracts are choking on real work

• You need to run heavy pricing, risk, or reconciliation logic (matrix math, batch signature checks, historical queries) “on-chain” to preserve auditability. But:
  • Writing lots of state dominates cost and latency; storage writes are the true bottleneck, not ALU ops. Even with Istanbul’s EIP‑1108 reducing BN254 precompile costs, verification and state updates still add up quickly. (eips.ethereum.org)
  • L2s are cheaper post‑EIP‑4844, yet compute remains constrained by gas limits and block timings; fees are volatile and blob market dynamics introduce new queuing/packing inefficiencies under load. (datawallet.com)
  • Your compliance team requires SOC 2/ISO 27001 evidence of access, change control, and data handling—hard to prove when “trusted servers” run in a black box. (aicpa-cima.com)

Agitation — The risks you’re already paying for

• Missed deadlines and overruns: naive on-chain loops or per-user proofs can blow block gas limits, forcing re‑architectures late in the program. EIP‑4844 lowered L2 data fees but not EVM compute ceilings, so CPU‑heavy tasks still stall timelines. (eip4844.com)
• Budget unpredictability: DA and calldata fees diverge by chain and by congestion. After Dencun, many L2s post blobs for pennies, but cost per MB still varies an order of magnitude; if you model with the wrong baseline, your unit economics break. (conduit.xyz)
• Compliance exposure: “we ran it off‑chain, trust us” won’t satisfy auditors evaluating SOC 2 Trust Services Criteria around processing integrity and availability. You need verifiable workflows and vendor‑neutral attestations—not screenshots. (aicpa-cima.com)
• Vendor lock‑in drag: choosing the wrong DA or off‑chain compute stack can lock you into opaque pricing or volume commitments just when usage spikes. Data shows alternative DA fees differ from Ethereum blobs by multiples, and pricing models keep evolving. (conduit.xyz)

Solution — 7Block’s decision framework and delivery method

We don’t argue ideology (“everything on-chain”). We profile your workload and route each part to the cheapest verifiable path that still clears your control and audit thresholds.

1. Decompose the workload

• Classify operations by their verification need and sensitivity:
  • Critical state transitions: keep minimal logic on-chain; optimize for reduced SSTOREs and succinct verification. (certik.medium.com)
  • Heavy but deterministic compute (hashing, batch verify, parsing, ML inference): offload with ZK proofs (Groth16/Plonk/STARK) via zkVMs and verify on-chain. (dev.risczero.com)
  • External data fetch/transform: use decentralized off‑chain compute with attestation (Chainlink Functions/CRE; TLSNotary/zkTLS where applicable). (docs.chain.link)
  • Bulk data posting: move to blobspace (EIP‑4844) or alternative DA (EigenDA/Celestia) based on your cost/throughput SLA. (eip4844.com)

1. Choose the right verifiable compute track

• On‑chain ZK verification economics you can actually budget:
  • Groth16 verification on Ethereum ≈ 207,700 gas + ~7,160 gas per public input; pairing checks are priced at 34,000·k + 45,000 gas after EIP‑1108. This is why we favor small public inputs and proof aggregation. (hackmd.io)
  • Aggregation layers: Aligned’s verification layer batches diverse proof systems and amortizes cost—~350k gas base per batch; ≈40k gas/proof at batch size ~20; milliseconds latency, with a BLS attestation on L1. Use this when you need throughput with “soft finality.” (blog.alignedlayer.com)
  • zkVM coprocessors: RISC Zero Bonsai wraps STARK outputs into Groth16 SNARKs for cheap on‑chain verify, ideal when your program is Rust/C++ and includes hard-to-code-in-Solidity logic (ed25519, HTML/JSON parsing). (dev.risczero.com)
  • SP1 (Succinct) path: for higher‑throughput Rust workloads with recursion and EVM verification; published figures cite ~275k gas to verify an SP1 proof on EVM, with ongoing real‑time proving advances. Use when you need frequent recursion or wish to standardize on a Rust toolchain. (succinct.xyz)

1. Data availability track (don’t pay for the wrong bytes)

• EIP‑4844 blob transactions place data in the beacon node for ~18 days with an independent fee market; multiple teams report sub‑$0.01 L2 fees for many tx types post‑Dencun. Use blobs when you settle to Ethereum and your data retention horizon fits blob TTL. (datawallet.com)
• If you’re moving serious MB/s, price out Celestia SuperBlobs or EigenDA:
  • Empirical cost per MB on Ethereum blobs averaged ~$20.56 (period measured by Conduit), while Celestia SuperBlobs for certain rollups ranged ~$0.46–$3.90/MB over May–Oct 2024. Evaluate by your batch size and posting cadence, not slogans. (conduit.xyz)
  • EigenDA publishes high throughput and updated pricing tiers; corroborate marketing claims with independent usage dashboards (e.g., L2BEAT) before procurement. (blog.eigencloud.xyz)

1. External data and private workflows

• Chainlink Functions/CRE lets you run decentralized off‑chain code, inject secrets via threshold encryption, and orchestrate cross‑system workflows. For regulated data, Chainlink’s Confidential Compute in CRE brings private compute with institutional orchestration (EA now, GA later 2026). Design your workflow so every step is attestable. (docs.chain.link)
• zkTLS/TLSNotary enables verifiable HTTPS session proofs so a contract (or a verifier set) can trust that “this JSON actually came from system X” without revealing secrets—useful for reconciling invoices, bank statements, or custodial records. (tlsnotary.org)

1. Security and compliance runway (SOC 2 + ISO 27001)

• We map your hybrid design to SOC 2 Trust Services Criteria (security, availability, processing integrity, confidentiality, privacy) and ISO 27001:2022 Annex A controls (secure coding, data masking, deletion, cloud services, monitoring). This is not paperwork—it drives how we implement verifiers, keys, logging, and vendor SLAs. (aicpa-cima.com)

1. Build, verify, and measure with 7Block

• Architecture, implementation, and audits across the stack:
  • Solidity and zk circuits with gas- and state‑aware design.
  • zkVM program development (RISC Zero/SP1) with CI proving.
  • DA integrations (blobs/EigenDA/Celestia) with cost guards.
  • Oracle/CRE orchestration for external systems with attestations.
  • Formalized runbooks and evidence for SOC 2/ISO 27001 audits.
• See how we execute end‑to‑end via our custom services:
  • Our custom blockchain development services
  • Our security audit services
  • Our blockchain integration
  • Our cross-chain solutions development
  • Our dApp development solutions
  • Our smart contract development solutions

Practical examples (with implementation detail)

Example A — Pricing engine with verifiable batch compute

• Scenario: Daily portfolio repricing over 20k instruments with proprietary adjustments. On-chain storage of every intermediate is cost‑prohibitive; pure off‑chain lacks auditability.
• Design:
  • Run pricing in a zkVM (RISC Zero or SP1), output a compact journal of final marks and a Groth16-wrapped proof. Verify on Ethereum; store only the final state delta. (dev.risczero.com)
  • DA: Post raw price vectors as blobs (EIP‑4844) during the challenge window; prune after ~18 days per blob TTL, while the immutable hash stays on L1. (datawallet.com)
  • Governance: CRE orchestration fetches vendor rates and FX via authenticated APIs; secrets are threshold-encrypted in the DON. (docs.chain.link)
• Why it wins:
  • On-chain verification gas scales with public inputs, not with instrument count; typical Groth16 verify is ~200–260k gas plus ~7k per public input. Keep public inputs to e.g., a Merkle root and a timestamp. (hackmd.io)
  • DA cost bounded and predictable; if blob pricing spikes, failover to alternative DA is available behind a feature flag (procurement‑approved). (conduit.xyz)

Example B — Multi-ERP reconciliation with private attestations

• Scenario: Monthly reconciliation across SAP, Netsuite, and bank APIs. Legal requires confidentiality; engineering needs proofs the data is authentic.
• Design:
  • Use CRE to orchestrate authenticated API pulls and hash commitments. For records requiring provenance, generate zkTLS/TLSNotary proofs of the HTTPS responses. (chain.link)
  • Contract accepts either a DON‑signed result or a TLSNotary proof; disagreements trigger a ZK recompute in a zkVM and a human review queue.
• Why it wins:
  • Meets SOC 2 “processing integrity” and “confidentiality” without revealing credentials or raw PII on-chain. (aicpa-cima.com)

Example C — High-throughput attestations with batched verification

• Scenario: Thousands of shop-floor IoT signatures per hour must be attested on-chain for warranty claims.
• Design:
  • Verify signatures or small ZK proofs off‑chain in a verification layer (Aligned), then submit a single BLS aggregate to Ethereum. Target ~350k gas for a small batch; ~40k gas/proof at batch size 20; read results next block. (blog.alignedlayer.com)
  • DA: For raw logs, price out Celestia SuperBlobs when sustained throughput pushes blob fees over an agreed ceiling. (conduit.xyz)

Emerging best practices we’re applying in 2026

• Treat “blobspace” as a finite queue, not a free lunch. Builders and rollups face packing inefficiencies (multi‑dimensional knapsack); smaller, more frequent blobs can reduce delay at high utilization. We tune batchers for this. (emergentmind.com)
• Use zk‑coprocessors for historical chain data. Axiom V2 demonstrated ZK‑verified queries over Ethereum history with a universal verifier; while Axiom pivoted product focus, the pattern stands and is viable with other stacks. (blog.axiom.xyz)
• Prefer proof aggregation or verification layers when you need “soft finality” and very high TPS; escalate to on-chain recursive proofs (“hard finality”) for end‑of‑day checkpoints. This hybrid cuts both gas and wall‑clock latency. (blog.alignedlayer.com)
• DA procurement is a portfolio decision. Keep Ethereum blobs as the default settlement path, but pre‑approve Celestia/EigenDA with caps and automatic failover rules. Monitor real usage (L2BEAT) versus vendor claims. (conduit.xyz)
• For Solidity that must remain on-chain, squeeze state, not just code:
  • Reduce SSTOREs; cache in memory; pack structs; prefer events over state for logs. These are still the highest‑impact savings, regardless of chain. (certik.medium.com)

Slim, verifiable reference snippets

Minimal on-chain Groth16 verify pattern (pseudo‑Solidity)

function commitAndVerify(bytes calldata proof, bytes32 journalRoot, uint256 ts) external {
    // 1) Verify Groth16 with tiny public inputs: [journalRoot, ts]
    require(Verifier.verifyProof(proof, [uint256(journalRoot), ts]), "bad proof"); // ~200k + ~14k gas

    // 2) Write a single state delta (emit event for the rest)
    commitments[journalRoot] = ts; // 1 storage write; avoid loops
    emit JournalCommitted(journalRoot, ts);
}

Use this with zkVM programs that emit the full journal off‑chain (e.g., in blobs) while keeping only the minimal root on L1 for audits. (hackmd.io)

What this means in business terms (proof with metrics)

• DA cost baselines you can model:
  • Ethereum blobs: observed averages around $20.56/MB over a long window (varies by rollup). Celestia SuperBlobs: $0.46–$3.90/MB for several rollups post‑launch window. Use these bookends for sensitivity analysis. (conduit.xyz)
• ZK verification cost you can plan:
  • Groth16: ~207,700 gas + ~7,160 gas per public input. Keep public inputs to O(1) via Merkle roots/commitments; avoid passing arrays as pubSignals. (hackmd.io)
  • Verification layer batching: ~350k gas per batch, ≈40k gas/proof at batch size 20; milliseconds operator latency and L1 read after one block. Ideal for “many small proofs.” (blog.alignedlayer.com)
• Post‑Dencun fee environment:
  • L2 fees materially lower due to blobspace with independent pricing; sub‑$0.01 fees are common in low congestion, but blob packing under load can re‑introduce delay/cost variance—design batchers accordingly. (datawallet.com)
• Compliance alignment:
  • Map workflow controls to SOC 2 Trust Services Criteria and ISO 27001:2022 Annex A new controls (secure coding, data masking, deletion, cloud services, monitoring) from day one; this shortens the audit cycle and eliminates rework. (aicpa-cima.com)

How 7Block runs this as a predictable program

• Discovery and profiling (1–2 weeks): quantify state writes vs compute vs data footprint; build a gas/DA TCO curve by path.
• Architecture and procurement (2–3 weeks): select ZK system (Groth16/Plonk/STARK via RISC Zero/SP1), DA mix (blobs/EigenDA/Celestia), and oracle orchestration (Functions/CRE). Draft SOC 2/ISO control mappings and vendor SLAs. (dev.risczero.com)
• Pilot build (6–8 weeks): implement minimal on‑chain verification, zkVM program(s), batcher, and DA adapters. Integrate with your ERP/BI via CRE and TLSNotary where required. Instrument KPIs: gas/tx, $/MB, p95 end‑to‑end latency. (chain.link)
• Security and launch (2–4 weeks): internal and external audits, invariant tests, incident runbooks, failover drills. Provide SOC 2/ISO 27001 evidence packs.
• Optional tracks: roll out your own OP Stack L2 if tenancy isolation or fee control is strategic; we harden the stack and integrate DA of choice. (docs.optimism.io)

What you’ll get in 90 days (Enterprise‑ready “money phrases”)

• “One‑click” cost guardrails: circuit‑level toggles that cap public inputs and fall back to verification layers when proofs spike.
• “DA abstraction”: switch between Ethereum blobs and alternative DA by policy; settle hashes to L1 for audit permanence. (conduit.xyz)
• “SOC2‑mapped workflows”: CRE‑orchestrated steps tied to Trust Services Criteria with logs and approvals. (chain.link)
• “State‑minimal contracts”: storage writes pared to the bone; everything else is verifiably off‑chain.

If you take only three actions this quarter

• Stop looping on-chain. Convert O(n) loops into O(1) proof verifications with roots and ranges as public inputs. (hackmd.io)
• Price data, not ideology. Model $/MB across Ethereum blobs vs Celestia/EigenDA for your actual batch sizes; pick a primary and a capped failover. (conduit.xyz)
• Replace “trusted servers” with verifiable off‑chain compute. Start with one critical report (pricing, reconciliation, or compliance) in a zkVM + CRE pipeline and measure p95 latency and gas/MB.

Relevant 7Block services to accelerate this

• End‑to‑end architecture and build: web3 development services, custom blockchain development services
• Verifiable compute and smart contracts: smart contract development solutions
• Security and readiness: security audit services
• DA and interoperability: blockchain bridge development, cross-chain solutions development, blockchain integration
• DeFi rails (if relevant to your program): DeFi development services, DEX development solutions

CTA — Book a 90-Day Pilot Strategy Call

Citations for selected claims:

• EIP‑4844 blobs, fee separation, and observed fee drops on L2s; queue/packing dynamics under load. (eip4844.com)
• Ethereum BN254 precompile gas repricing (EIP‑1108). (eips.ethereum.org)
• Groth16 verification gas formula. (hackmd.io)
• Verification layer batching economics and throughput. (blog.alignedlayer.com)
• zkVM coprocessors (RISC Zero Bonsai on Ethereum) and SNARK wrapping. (dev.risczero.com)
• DA cost comparisons and Celestia SuperBlobs data. (conduit.xyz)
• EigenDA status, throughput claims vs independent dashboards. (blog.eigencloud.xyz)
• Chainlink Functions/CRE and Confidential Compute timeline. (docs.chain.link)
• TLSNotary/zkTLS for verifiable HTTPS. (tlsnotary.org)
• SOC 2 Trust Services Criteria; ISO 27001:2022 Annex A control updates. (aicpa-cima.com)

Book a 90-Day Pilot Strategy Call