Inco
AI NativeInco brings fast, programmable privacy to blockchains, protecting address and transaction details across key use cases.
Est 2023|Valuation $8M|Raised $10.3M
Inco brings fast, programmable privacy to blockchains, protecting address and transaction details across key use cases.
Published Jun 25, 2026
| Starting Price | No public SaaS tiers; protocol fees for certain operations (native gas + Inco fees) | Varies by deployment/usage; primarily tooling/coprocessor model (pricing not standardized publicly) | Network gas fees; ecosystem-specific costs (no SaaS tiers) |
| Suitable for | Developers seeking confidentiality features integrated with existing chains; applications needing encrypted state + access control | Teams building FHE smart contracts/coprocessor-enabled apps; FHE-first approach | EVM developers wanting confidential compute via TEEs in a standalone network environment |
| Key Strength | Modular confidentiality layer concept; combination of multiple cryptographic techniques; developer templates and EVM/SVM tooling described in documentation | FHE research and product focus; provider of core FHE libraries and fhEVM products | TEE-based confidentiality may deliver lower-latency compute; established network history and documentation |
| Key Weakness | Early-stage/beta indicators; limited publicly documented enterprise compliance artifacts; unclear production track record | FHE complexity and performance constraints; developer learning curve | TEE trust model considerations and potential hardware vulnerability classes |
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Inco and Zama: Inco can be characterized as an application/network layer that integrates FHE and other techniques; Zama provides core FHE libraries and fhEVM components. If Inco depends on external FHE libraries, that dependency introduces supply-chain and roadmap coordination considerations.
Inco and Fhenix: Both operate in the FHE + EVM design space; differentiation may depend on developer UX, performance strategies, and partnerships. Fhenix provides developer guidance on gas and benchmarks that can assist cost modeling.
Inco and Oasis/Secret: TEE-based ecosystems can provide lower-latency confidential compute but rely on hardware trust assumptions. Inco’s multi-technique approach (TEE + FHE + MPC) indicates an attempt to balance performance and cryptographic guarantees, but also increases system complexity and the need for clear threat modeling.
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