NEAR protocol artificial intelligence development platform Explained

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NEAR protocol artificial intelligence development platform

This section introduces a practical foundation for AI‑native applications that need dependable blockchain guarantees and a modern developer experience for US enterprises.

Think of the stack as two parts: a user-facing AI layer that guides intent and a secure backend that handles identity, trust, and data. The chain acts as the execution bed so agents can own assets, make decisions, and transact across networks.

The architecture uses Nightshade sharding and Doomslug consensus to deliver sub-second blocks and ~1.2 s finality. That design keeps fees low and throughput reliable for real users and enterprise applications, while wallets and tokens enable smooth commerce across the world.

Built for the future: mature tooling, education programs, and production services speed time-to-value. Services cover discovery, architecture, build, and run phases to help regulated US teams scale with predictable cost, performance, and compliance. Illia Polosukhin’s leadership ties the system to state‑of‑the‑art agent and model design.

Key Takeaways

  • Provides a secure execution environment where agents manage assets and actions.
  • Combines an AI front end with a verifiable blockchain backend for trust.
  • Uses sharding and fast consensus for real‑world speed and low fees.
  • Mature ecosystem and tooling reduce integration risk and speed delivery.
  • Commercial services aim to optimize cost, compliance, and performance.

Powering AI‑native applications with NEAR’s agentic execution layer

This execution runtime turns intent into verifiable on‑chain actions. It is the runtime where agents own identity, wallet custody, and enforce business policies across networks. The design lets models act without human handoffs while preserving traceability.

Agents that own assets, make decisions, and transact

Agents maintain wallets, hold permissions, and initiate transactions to complete tasks end‑to‑end. Decision loops let an agent interpret intent, score options, and trigger both on‑chain and off‑chain interactions that remain auditable.

Blockchain as the backend, AI as the user interface

The blockchain supplies keys, signatures, and access control while the AI front end organizes user intent into structured workflows. Asset custody and policy enforcement ensure agents operate within regulatory and privacy constraints.

  • Cross‑network tasks: payments, settlements, and attestations.
  • Low‑latency execution integrates identity with settlement.
  • Unified accounts and contract calls simplify API and on‑chain calls.
CapabilityWhat it providesEnterprise benefit
Identity & accessKeys, signatures, role checksTraceability for decisions
Asset custodyWallets, permissions, escrowCompliance and privacy controls
ExecutionFast settlement, contract callsReal‑time responses and audit logs

Service overview: Enterprise‑grade NEAR AI development for the United States

This service overview outlines how enterprise teams move from strategy workshops to steady run operations with measurable outcomes. We emphasize controls, repeatability, and fast feedback loops so US organizations can ship secure applications at scale.

A professional team of software engineers and data scientists collaborating in a modern, well-lit office setting. Desks and workstations arranged in an open floor plan, with large windows letting in natural light. In the foreground, several employees are intently focused on their computer screens, hands on keyboards. In the middle ground, a small group gathered around a whiteboard, discussing technical diagrams and visualizations. The background features a sleek, minimalist design with clean lines and muted colors, conveying a sense of efficiency and enterprise-grade capabilities. The overall atmosphere is one of focused productivity, with a hint of innovation and cutting-edge technology.

From strategy to deployment: discovery, architecture, build, and run

Full‑lifecycle delivery includes strategy workshops, solution discovery, secure architecture design, and a build phase that hands over to run operations.

Deliverables map to developers need: reference architectures, runbooks, IaC templates, and integration guides for core systems.

Compliance‑conscious delivery tailored to regulated industries

Solution patterns cover agent‑driven customer service, automated settlements, and identity‑aware data exchanges. Each pattern ties to measurable KPIs for latency, throughput, and cost per transaction.

  • Governance from day one: role‑based access, key management, and auditable release workflows.
  • Tooling stacks for CI/CD, observability, and policy enforcement to reduce operational complexity.
  • Run operations: incident management, capacity planning, change control, and monthly business reviews.
PhaseCore deliverableEnterprise benefit
DiscoveryWorkshops, use case mappingAligned scope and risk profile
BuildReference code, IaC, testsRepeatable, auditable deployments
RunRunbooks, SLAs, cost reportsPredictable performance and ops

Design choices leverage the underlying protocol to keep behavior predictable in production. This approach balances rapid iteration with the end‑to‑end controls required by regulated industries and integrates with the broader ecosystem and existing platforms.

Why NEAR for AI: open, permissionless, and mass‑market ready

Open participation and predictable economics make this stack ready for mass adoption by enterprises and indie builders alike.

A lush, verdant ecosystem teeming with life. In the foreground, a diverse array of flora – vibrant flowers, towering trees, and cascading vines. Dappled sunlight filters through the canopy, casting a warm, golden glow over the scene. In the middle ground, a pristine stream meanders through the landscape, its crystal-clear waters reflecting the surrounding greenery. Overhead, birds soar gracefully, their calls echoing through the tranquil air. In the distance, rolling hills and towering mountains rise up, creating a serene and majestic backdrop. The overall atmosphere is one of balance, harmony, and the interconnectedness of all living things.

Permissionless access lets teams iterate without gatekeepers. Developers and enterprise engineers can deploy agents, test flows, and scale without lengthy approvals. This access model supports both global and US‑based users who need clear economic and operational predictability.

Verifiable compute and privacy-preserving interactions

Verifiable compute patterns anchor agent outputs to on‑chain proofs for auditability. That lets auditors and regulators validate decisions without exposing raw data.

Selective disclosure pairs cryptographic attestations with identity controls. Sensitive data stays private while proofs provide the necessary compliance evidence.

Low fees, high speed, and fast finality for real-world users

Low transaction costs and ~600 ms blocks with ~1.2 s finality deliver a responsive user experience. These characteristics meet web‑scale expectations for performance in the real world.

Production tooling for agents that ship

SDKs, docs, and integration tooling reduce time to production. The ecosystem emphasizes outcomes: agents that operate reliably and scale with consistent uptime.

FeatureWhat it enablesBenefit for teams
Permissionless accessOpen deployments, fast experimentsLower time-to-market and flexible governance
Verifiable computeOn-chain proofs, cryptographic attestationsAuditability without leaking private data
Sharding & optimized consensusSustained throughput under loadPredictable performance and lower costs
Production SDKsReference code, CI/CD integrationsRepeatable, auditable agent rollouts

Architecture and performance: Nightshade sharding and Doomslug finality

A split‑shard architecture and fast finality work together to remove single‑threaded bottlenecks and deliver steady throughput for agentic systems.

Parallel execution, throughput at scale, and sub‑second blocks

Nightshade sharding splits state and compute into parallel shards so smart contracts run simultaneously instead of queuing on one ledger. This reduces contention and raises theoretical throughput toward 100,000 TPS while keeping per‑transaction latency low.

Doomslug enables ~600 ms block times and ~1.2 s finality, giving deterministic confirmation windows that improve reliability for mission‑critical services.

Designing agents for shard‑aware smart contracts

Shard‑aware contracts minimize cross‑shard calls and batch messages to cut inter‑shard overhead. Chain‑level scheduling and ordered message passing ensure multi‑contract workflows remain predictable under load.

  • Profile hot paths to place related state on the same shard.
  • Model gas for cross‑shard messages and test worst‑case latency.
  • Use async receipts and idempotent handlers to simplify retries.
MetricTypical valueImpact on UX
Block time~600 msLow visible delay for actions
Finality~1.2 sDeterministic confirmations for flows
ThroughputTheoretical up to 100k TPSConsistent service under load

Developer implications: add profiling, gas modeling, and shard‑aware testing to CI so contracts coordinate state predictably. Distributing compute across the network helps keep costs stable as activity grows and enables a scalable foundation for agentic applications on the NEAR protocol.

NEAR protocol artificial intelligence development platform services

Our services turn user intent into resilient, auditable actions across on‑chain and off‑chain systems. Teams receive design patterns and engineering delivery to accelerate safe production for enterprise use. The focus is on traceability, repeatability, and measurable controls.

A sleek and modern data pipeline, with clean lines and a minimalist aesthetic. In the foreground, a series of interconnected modules represent the various stages of data processing, from ingestion to transformation and analysis. The middle ground features a network of pipes and tubes, symbolizing the flow of information between these components. In the background, a futuristic cityscape with towering skyscrapers and a vibrant, neon-lit skyline creates a dynamic and technologically advanced backdrop. The lighting is crisp and directional, casting sharp shadows and highlights that accentuate the mechanical nature of the data pipeline. The overall composition conveys a sense of efficiency, innovation, and the power of NEAR protocol's artificial intelligence development platform.

Agent design: intent capture, decision models, and automated actions

Agent design services capture user intent, map business rules, and select the right decision model for each flow. We orchestrate automated actions that combine on‑chain calls and off‑chain integrations.

Smart contracts, identity, and trust layer integration

Contracts implement identity, permissions, and policy enforcement. Key management, role‑based access, and audit trails align with enterprise security requirements.

Data pipelines for model inputs and on‑chain verifiability

Data pipelines feed feature stores and model inputs while recording verifiable outputs. Outputs link to cryptographic attestations so decisions remain auditable for compliance and incident response.

  • Developer tools: SDKs, testing harnesses, and observability to speed safe iteration.
  • Resilient systems: retries, idempotency, and multi‑region failover for uptime.
  • Execution efficiency: map high‑frequency calls to shard‑aware designs to keep latency and costs predictable.
ServiceWhat it deliversEnterprise benefit
Agent designIntent capture, decision model selectionFaster time‑to‑market and consistent actions
Trust infrastructureKey mgmt, RBAC, audit logsRegulatory alignment and clear accountability
Data pipelinesFeature stores, verifiable outputsReproducible decisions and compliant evidence

Governance and ops include model and contract versioning, rollback processes, and documented decision proofs. These services integrate with the broader ecosystem to shorten time‑to‑production and give developers predictable, secure infrastructure.

Read more on the intersection of crypto and AI for context on applied use cases and tooling.

Interoperability and tooling across ecosystems

Cross‑chain tooling lets teams move apps and tokens between networks with predictable steps and known risks. This section outlines practical paths for porting Solidity code, moving assets, and operating multi‑chain topologies.

Interactions: a seamless dance of protocols, platforms, and tools. In the foreground, digital assets flow effortlessly between decentralized ecosystems, bound by smart contracts and APIs. The middle ground showcases interoperable interfaces, allowing developers to build applications that span boundaries. In the background, a vibrant network of open-source libraries and developer tools hum with activity, empowering collaboration and innovation. Warm lighting accentuates the organic fluidity of this interconnected landscape, while a wide-angle lens captures the expansive potential of cross-chain harmonization.

Aurora: EVM compatibility and migration paths

Aurora provides EVM compatibility so teams can port Solidity applications with minimal code changes and retain familiar tooling and wallets.

Built‑near migration paths reduce time and risk when adding a new execution venue or moving from other platforms.

Rainbow Bridge: tokens and cross‑chain interactions

Rainbow Bridge moves tokens and messages across chains to unlock liquidity and data portability.

Operational notes: watch fees per transfer, confirm bridge finality rules, and automate retries for stalled transfers.

Octopus and multi‑chain strategies

Octopus enables domain‑specific chains that coordinate with a main network for settlement. This supports complex systems that need local throughput and global settlement.

  • Typical transactions: token transfers, wrapped asset mint/burn, cross‑chain calls and event relays.
  • Patterns: token wrapping, allowance checks, replay protection, and bridge confirmation runbooks.
  • Trade‑offs: sharding boosts throughput but adds coordination latency for cross‑shard interactions.
RouteFeesSecurity considerations
Aurora (EVM)Low to moderateFamiliar tooling, standard audits
Rainbow BridgeVariable bridge feesWatch finality, monitor relayers
OctopusDepends on app chainCross‑chain governance and settlement checks

Tokenomics in practice: fees, staking, and governance for AI operations

Managing token flows and incentives makes agent operations predictable and secure. Cost modeling helps teams forecast per‑task spend, set budgets, and tune agent behavior.

Optimizing transaction costs and throughput for agents

Batching calls, scheduling low‑priority work off‑peak, and minimizing on‑chain writes reduce fees. Use async receipts and idempotent handlers to limit retries.

Operational tips: meter transactions per agent, cap daily budgets, and alert on spend spikes.

Staking and validator alignment for performance and security

Tokens fund validator rewards and governance. Strategic staking aligns incentives so validators prioritize uptime and low latency.

  • Separate operational float from treasury holdings for clear custody.
  • Use multi‑sig wallets and automated custody rules for agents and org accounts.
  • Monitor validator health and decentralization to manage risk.
AspectWhy it mattersAction
Fees & transactionsDirect operating costBatching, scheduling, caps
Staking & validatorsSecurity and performanceStake tuning, diversify validators
Wallets & custodyAccess control for assetsMulti‑sig, policy automation

Security, privacy, and data integrity by design

A zero‑trust approach combined with verifiable outputs makes agent actions transparent and defensible. Security and privacy are core design goals. Systems should provide proof, not just logs.

Verifiable compute and zero‑trust patterns for AI agents

Link model outputs to on‑chain attestations so each decision has a verifiable trace. Use signatures or proofs to anchor results for audits.

Enforce least privilege, segmentation, and continuous verification between services. Treat every component as untrusted until proven safe.

Wallets and key management for users, agents, and organizations

Adopt hardware wallets and HSMs for critical keys and use software wallets with strict seed controls for agents. Rotate secrets, enforce multi‑sig for high‑value actions, and limit token spend per agent.

  • Encrypt data at rest and in transit; enable selective disclosure for audits.
  • Use secrets-management tools, rotation policies, and tested recovery plans.
  • Run threat models for end‑to‑end flows and prepare incident playbooks with post‑mortems.
AreaActionBenefit
Compute attestationsSign outputsAuditability
Key opsHSM & rotationReduced compromise risk
OperationalPhishing‑resistant MFAUser protection

Ecosystem strength: developers, education, and community momentum

A vibrant ecosystem and focused education paths help teams ship production apps faster. Short courses, mentorship, and public events feed a steady stream of talent. The network reached 46 million monthly active users by mid‑2025, showing real traction across the world.

NEAR University and Academy for developer enablement

Structured learning is an on‑ramp for engineers and product teams. NEAR University and NEAR Academy provide hands‑on labs, sample code, and certification tracks so developers gain skills that match production needs.

  • Bootcamps and tutorials for fast onboarding.
  • Mentorship and hackathons that form teams and prototypes.
  • Docs and sample apps that cut prototype time for developers need to ship.

Foundational leadership: Illia Polosukhin and an AI‑native vision

Illia Polosukhin brings research credibility and a product vision that ties model design to developer experience. That leadership steers tooling, grants, and public events toward use cases with measurable value.

AreaBenefitExample
EducationFaster ramp for teamsBootcamps to production
CommunityProject formationHackathons and grants
PerformancePredictable costs & latencyFinance, gaming, identity

Cross‑chain tools and open platforms ensure ideas can move between blockchains. US teams should leverage these resources to build enterprise‑grade applications with confidence.

Engagement model: how we build AI-native apps on NEAR

We start each engagement by mapping business value to a clear set of KPIs that guide product and engineering choices. This ensures chosen use cases deliver measurable outcomes and fit timeline constraints.

Use case selection, KPIs, and success criteria

We score ideas on impact, effort, and operational risk. Each selected application gets target KPIs for latency, throughput, cost, and user adoption.

Pilot-to-production roadmap with performance SLAs

Pilots follow gated stages: prototype, pilot, canary, and full launch. Each gate has SLAs tied to performance and rollback criteria that match enterprise standards.

Architecture reviews examine execution flows, sharding effects, and contract composition to reduce complexity. Reference contracts and test suites validate reliability before scaling users.

PhaseDeliverableEnterprise control
DiscoveryUse case scorecard, KPIsValue alignment
PilotPerformance SLA, test planRollback & error budget
ProductionRunbook, observabilityCost tracking & compliance sign-off

Agents are instrumented for telemetry, policy checks, and safe recovery. Capacity planning uses protocol characteristics like sharding and block finality to size resources. We keep stakeholders aligned with clear docs and ongoing status updates, and link practical context in this platform primer.

Shape the agentic future with NEAR—start your AI project today

Start your agentic program on a fast settlement layer that shows the true power of the future for enterprise use.

Built near systems deliver sub‑second blocks, predictable finality, and low fees so user flows feel instant in the real world.

Establish organization wallets, custody rules, and staking plans early to secure operations and control token spend.

Leverage mature tooling, education, and cross‑chain interoperability to reduce launch risk and meet SLAs from pilot to production.

Book a discovery session to align use cases, KPIs, cost models, and a timeline to production. This approach positions teams to build verifiable, privacy‑respecting, and scalable blockchain solutions that endure.

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