Private buyer page for Snowflake

Snowflake is becoming an agentic control plane.

Maya has ninety minutes.

Snowflake is connecting governed data to agent action. The next requirement is proof an outside reviewer can verify.

Maya is a data governance lead at a regulated financial institution. Audit asks about a fourteen-month-old Snowflake CoWork action that read customer records, sent a Slack summary, and opened a Jira ticket.

She has to answer who authorized it, which rule allowed it, what data it read, and where the information went. Maya does not need another dashboard. She needs a record an independent reviewer can check.

Runs locally after page load No login for the verifier

One proof record. One answer an outside reviewer can check.

Who was authorized: the approved Snowflake service identity and reviewer scope.

Which rule applied: the exact policy version active at the moment of action.

What the agent did: the governed read and the summary it prepared.

Where the result went: Slack delivery and the Jira escalation.

When it happened: the signed event time an outside reviewer can verify later.

Overview poster

From Snowflake control plane to portable proof.

Snowflake already brings governed data, lineage, identity direction, and observability. As CoWork and service agents move from intent to real action, the buyer question becomes whether the full chain can still be proven outside Snowflake when the workflow reaches Slack, Jira, or another system.

Hive does not replace Snowflake governance. Hive adds an independently signed proof record that can travel outside the platform and still be checked later.

13,912 total customers as of April 30, 2026.
40% of the Forbes Global 2000 as of January 31, 2026.
July 23, 2026 SERVICE_AGENT reached general availability.
365 days of Account Usage history, with up to 180 minutes of ACCESS_HISTORY latency.
Transformation map

The new control question is whether an outside reviewer can prove the whole chain later.

Snowflake remains the operator
01

Governed data and policy stay in Snowflake.

Horizon Catalog, lineage, and the service identity surface remain the operating context.

Governed context
02

Snowflake CoWork turns intent into action.

An agent reads a regulated dataset, summarizes findings, and drives a real downstream workflow.

Agent action
03

The ordinary audit trail is still platform-produced and time-bounded.

Snowflake documents one year of Account Usage history, up to 180 minutes of latency, and published exclusions.

Useful record
04

Hive binds authority, rule, read, and delivery into one portable proof file.

Carnac and Imprimatur capture permission and policy. SiGR, AFiR, and R3Pv seal the workflow for later review.

Independent proof
05

Maya answers in minutes instead of reconstructing the story across systems.

The proof file survives the moment when the question moves outside Snowflake and into audit, counsel, customer review, or regulatory review.

Outside review

Snowflake governance is real. Hive adds the second record another party can verify without trusting the platform alone.

01
Snowflake already governs your data well

Snowflake is already connecting identity, governance, and action.

This page does not argue that Snowflake is weak. It assumes Snowflake governance matters, that CoWork and agentic work are real, and that Hive belongs beside that control plane rather than in place of it.
Snowflake first

Hive starts from Snowflake strength, not from a teardown.

Snowflake positions itself as the control plane for the agentic enterprise. It already has Horizon Catalog as a governance layer, Trust Center detections as a posture surface, and SERVICE_AGENT in general availability. Hive keeps all of that in place and adds one independent proof record that can travel outside the platform.

Governance and lineage are already part of the Snowflake story.

Horizon Catalog is the trust layer Snowflake wants buyers to rely on across data inside and outside the platform.

Identity is moving closer to the agent surface.

SERVICE_AGENT is now GA, and Snowflake has published a broader agent identity direction for enterprise AI.

Intent is becoming action.

CoWork is the important shift. Once the agent can act across enterprise systems, the audit question changes from access alone to proof of the whole workflow.

02
The record stops at the edge, and expires

The ordinary record is useful. It is still time-bounded and platform-produced.

Snowflake's own documentation is the key evidence here. Account Usage keeps one year of history. ACCESS_HISTORY carries up to 180 minutes of latency and published exclusions. When the workflow reaches Slack and Jira, the review path is already split across systems and retention windows.
What Snowflake documents

The documented trail is valuable, but it still leaves Maya reconstructing the answer.

  • 365D
    One year of Account Usage historyA fourteen-month question already sits beyond the ordinary platform window Snowflake documents.
  • 180M
    Up to 180 minutes of ACCESS_HISTORY latencyThat is fine for operational telemetry. It is not the same thing as one immediate proof file.
  • EXCL
    Published exclusions and truncation behaviorSnowflake documents failed queries, replication-driven movement, stream updates, RESULT_SCAN, partial view chains, some Native App redaction, and truncation behavior.
  • EDGE
    The workflow continues outside SnowflakeSlack and Jira delivery matter to the answer, but they live in separate systems with separate exports, admins, and retention settings.
03
Same platform. A record anyone can check

Keep Snowflake as the operator. Add one proof layer another party can verify.

Snowflake keeps the governed dataset, service identity, policy context, lineage, and observability. Hive adds a proof layer that seals authority, identity, action, and downstream delivery into one record an outside reviewer can check later.
Snowflake continues to operate
  • Governed datasetHorizon Catalog, lineage, policy context, and table controls remain where they already live.
  • Service identitySERVICE_AGENT and the Snowflake operating surface still own execution.
  • ObservabilityTrust Center and Account Usage still matter for posture and operations.
Portable proof

Authority, action, proof, review, repeat.

Hive binds who was allowed to act, which rule applied, what the agent did, and where the information went into a small signed file that can be checked outside Snowflake.

Carnac / Imprimatur HiveBound / SPIRE / S2S SiGR / AFiR-S3 R3Pv
Outside reviewer verifies
  • AuthorityWho authorized the workflow and what reviewer scope applied.
  • RuleWhich policy version allowed the action to continue.
  • Read and deliveryWhich governed dataset was read and where the downstream effect landed.

Carnac and Imprimatur decide and clear the action before it fires. HiveBound, Agent Trip & SPIRE and S2S bind identity, trajectory and silicon. SiGR and AFiR-S3 sign the decision and each autonomous step. R3Pv then binds authority, read, action and downstream delivery into one signed decision vector, so a reviewer is not left inspecting fragments. Snowflake stays the governed data and action surface throughout. Hive adds a proof layer beside it, never in front of it. The next section maps every Snowflake surface that produces an effect to the instrument that makes it checkable. The section after that covers the seven controls that run before the effect at all.

04
Surface by surface correlation

Every Snowflake surface that produces an effect has a matching proof instrument.

This is the full map. On the left, Snowflake capability described in Snowflake’s own words. On the right, the Hive primitive that makes the same event checkable by someone who does not trust either party. Nothing on the left is a criticism. Everything on the left is why the right side matters.
The distinction

Snowflake is not missing governance. Snowflake cannot be an independent witness to Snowflake.

Horizon Catalog carries lineage, data quality monitoring, sensitive data classification and AI guardrails. Cortex Agents run under existing roles and privileges. Snowflake states the position plainly:

Governance policies execute at the query engine layer, not the application layer. They apply automatically to every caller: human analyst, BI tool, or AI agent.

That is a strong control surface, and it is not the same thing as evidence.

Why a second layer exists

The record and the operator are the same party.

Everything the platform records is the platform’s account of its own behaviour, stored inside itself, verified by itself. For operations that is exactly right. For an auditor, a regulator, a counterparty or opposing counsel, it is the one form of proof they are trained not to accept on its own.

Hive adds the part no operator can supply about itself. A post-quantum signed record that leaves the platform, survives outside it, and verifies without it.

patent pending Left column quoted verbatim from Snowflake documentation Right column is Hive Proof Architecture, unchanged for this audience
Before the model runsSnowflake decides what the agent may do. Hive signs that decision before the effect.
Snowflake Intelligence and CoWork turn intent into real action As agents move from answering to acting, each consequential call needs a proof decision made before it fires.
Carnac™ Control Plane

Sits before any model and before any consequential effect. Reads consequence and routes each call to the proof it warrants. It does not replace the proof architecture. It conducts it.

The business question arrives as natural language Everything downstream inherits that request. The phrases carrying legal, financial or privacy weight are not marked at the moment someone types them.
Carnac Live Ink™

Marks the spans of a request that need context, proof or permission, and preserves the user’s words byte for byte. The selected authority binds into the receipt before submit, so intent is recorded evidence rather than later recollection.

The plan step assembles the context the model will see The agent parses the request and decides how to answer it.
CarnacPrompt™

Commits the assembled prompt window before the model runs, so what the model was shown is a fixed object rather than a later reconstruction.

SERVICE_AGENT and role-derived session permissions Cortex Agents determines session permissions from the querying user’s default role.
HiveBound™

Wraps the call in a signed envelope declaring identity, intent and budget before inference runs. The claim travels with the record once it leaves Snowflake.

Privilege checks before an agent runs Calling an agent requires the SNOWFLAKE.CORTEX_USER or SNOWFLAKE.CORTEX_AGENT_USER database role, privileges on the agent object, and privileges on the objects used by the agent’s tools.
Imprimatur™

Signs a clearance before the call runs and refuses any call without a valid unexpired pass. The check is proven up front, not inferred from a log afterwards.

Inference and model proofSnowflake runs the model. Hive signs which model ran, on what, and to what end.
Cortex model inference on GPU Confidential computing attests the accelerator once, at startup.
S2S™ · Silicon-to-Signature

Binds every inference into a hash-chained attestation epoch anchored to hardware evidence and a Hive nonce. Startup attestation becomes per-call attestation.

Cortex Analyst generates SQL from a semantic view Generates SQL queries over your structured data from natural language, using a semantic view.
SiGR™ · Signed Inference Guarantee Receipt

Signs the decision itself, meaning model, inputs and outcome, into one ML-DSA-65 receipt anchored on Base. The atom of the whole stack.

Threads persist conversation context across turns Threads maintain conversation context across turns, so your client application doesn’t have to manage state.
MiR™ · Model Identity and Relineage

Signs which model actually served each turn of a persistent thread and detects substitution against the model you contracted for, scoring identity instability across the thread. A long-lived thread is exactly where a silent model swap hides. Asserts model identity and continuity only, never output quality.

The agent splits a complex request into subtasks Split a complex request into subtasks.
AFiR™ · Attested Fragmented Inference Routing

Breaks the request into signed routable sub-tasks and signs each fragment inside the inference path, so a multi-step answer is provable at fragment level.

Cortex Search retrieves from unstructured sources Retrieves information from your unstructured data.
AFiR-OCR DocProof™

Proves what a document model read, where on the page, and at what confidence. The extracted value stays bound to its source region.

Agents in motionSnowflake orchestrates the loop. Hive receipts every stop on the route.
The plan, act, reflect loop repeats inside one request The agent repeats this loop as needed within a single request.
AFiR-S3™

Signs tool scope, action, context mutation and reward around every autonomous step. The workflow becomes an audit trail, not a transcript.

MCP connectors reach tools hosted outside Snowflake Tools hosted on remote Model Context Protocol (MCP) servers, such as those from Atlassian Jira, Salesforce, or your own applications.
SmartAgent Route Graph™

Follows the agent across every model, provider, tool and payment stop, each emitting its own receipt. Route proof, not just a final answer.

The code execution tool runs Python in a sandbox Runs Python in a secure, isolated sandbox to process data and perform calculations.
PBS™ · Provenance-Bonded Sandbox

Binds container image, kernel modules, package index, egress ACL and GPU firmware into a Merkle heartbeat chained across the life of the environment.

Agent toolsets inherit tools from other agents at run time References to other agents whose tools are inherited at run time, enabling modular and composable agent architectures.
Agent Trip & SPIRE™

Signs agent-instance mints, trajectories and coherence as FIPS 204 receipts, so inherited authority stays attributable.

Custom tools call backend systems outside the platform Stored procedures and user-defined functions (UDFs) that implement your own business logic or call backend systems.
Arrival Countersignature™ · Carnac Gateway™

Compares the approved action tuple against the one actually delivered. Match and the gateway countersigns. Any change, replay, wrong destination or broken chain is recorded as a delta.

Guardrails, egress and evidenceSnowflake enforces the rule. Hive proves the rule was the one enforced.
AI Guardrails act on agent output Detect, redact, and block personally identifiable information (PII) and protected health information (PHI) from agent outputs.
Refusal Ledger™

A chained Merkle ledger of every refusal-policy change, with a Pedersen commitment and zk-SNARK bond proving the runtime policy sat inside a published band at the moment it mattered, without disclosing the policy.

The web search tool reaches the public internet Real-time information from the public internet. Must be enabled at the account level.
Egress Bond™

Additive Pedersen commitments meter outbound exposure by semantic class, covering credential, PII, model weight, test data and plaintext, against caps committed in advance.

The loop is designed to stay inside the secure perimeter Staying within Snowflake’s secure perimeter.
Perimeter Bond™

Every egress-attempt receipt embeds the SHA-256 of the compiled eBPF enforcement bytecode, so a silent gap between the declared perimeter and the running one is visible.

Access history and Time Travel support later review Role-based access controls, Time Travel, and access history let you review past activity and data states.
Forensic Rail™

Investigation runs under a threshold-signed k-of-n credential and every model call under it is replay-bonded, so the investigation is itself evidence.

Agents execute on their own schedule, including out of hours Autonomous execution does not pause for the oversight calendar.
Diurnal Bond™

Consequential actions in weekend, on-call, after-hours and incident windows require k-of-n countersigning from distributed attestors, with k raised as oversight thins.

Sharing, lineage and settlementSnowflake moves the data. Hive keeps the proof portable once it lands elsewhere.
Column-level lineage reaches beyond the platform Column-level lineage across Snowflake, external databases, BI tools, and OpenLineage feeds.
R3Pv™ · Receipt Proof Vector

Rolls the receipts for one event into a single signed decision vector: verification depth, weakest boundary, recoverability, next action. One answer, not a pile of fragments.

Governance follows data into Iceberg and Marketplace Governance policies follow your data to Iceberg tables and Snowflake Marketplace. Shared data products carry their tags and permissions.
OriginProof™

Binds the conditions under which a data product was produced, covering credentials, session, tools and output, so a consumer can check origin without trusting the distributor.

Clean rooms let parties collaborate without exposing data The value of the collaboration depends on nothing leaking, including into the audit trail.
Disclosure-Free Replay™

Reconstructs the exact route and cue-delta without revealing the prompt, the data or the words. Auditability and confidentiality stop being a trade.

Consumption is metered and billed per workload Agentic workloads make the bill itself a thing counterparties question.
Hive Receipt™

Spectral-signed settlement receipts with on-chain verification and an MCP endpoint, so payment carries the same standard of evidence as the decision behind it.

Account Usage retains one year of history for later review A searchable index inside the platform answers operational questions well. It remains the platform’s index of the platform’s own behaviour.
Hive Ledger™

A searchable index across every receipted event, queryable by sequence, event type and time. It is the convenience layer and not the proof. Each row points back to a receipt that verifies on its own, so if the ledger is unreachable the receipts still check.

Quoted text on the left is taken verbatim from Snowflake product documentation, linked in full in the source section at the end of this page. Underneath every primitive on the right sit InkFrame v1, the content-addressed envelope sealed by its own hash over RFC 8785 JCS and SHA-256, Hive Typed Signer, the shared ML-DSA-65 engine, and HiveSeal · QPuF, a signing device that keeps the key in silicon. Primitives marked are patent pending. Hive Ledger is a convenience index and carries no patent claim. Hive does not operate, replace or sit in front of Snowflake governance, and a signed record that a rule ran is not a statement of legal, regulatory or compliance status.
05
Pre-effect controls · the upstream seven

Seven controls that run before the effect, on the customer’s half of shared responsibility.

Section 04 maps Snowflake surfaces to instruments that make a completed decision checkable. These seven sit earlier. They prove a rule was enforced before the action ran, and refuse the action when the proof is missing or stale. Same rule as the rest of this page: nothing on the left is a criticism, and everything on the left is why the right side matters.
Snowflake draws the line itself

Snowflake states plainly that some obligations are the customer’s, and these seven live there.

The shared responsibility model is Snowflake’s own framing, not an outside critique:

The Shared Responsibility Model defines the specific security obligations of both the customer and Snowflake.

Snowflake names hardening account configurations and managing access controls for sensitive data among the controls the customer implements and manages. Snowflake also states its guiding principle is to minimise the customer’s obligations under that model. Both things are true at once, and what remains on the customer side is exactly where these seven instruments operate.

Why these seven are a different kind of thing

A log tells you what happened. A control stops it from happening.

Every instrument in section 04 turns an event into a signed exhibit that survives outside the platform. That answers the question after the fact, and answering after the fact is worth a great deal.

These seven answer a different question. They sit in front of the action and refuse it. An auditor does not give credit for a log, and a regulator does not give credit for telemetry. They give credit for a control that can be shown to have been enforced.

The distinction matters most where an agent acts on its own. Reconstructing an unauthorised action is not the same as it having been impossible.

patent pending Left column quoted verbatim from Snowflake documentation Right column is Hive Proof Architecture, unchanged for this audience
Before the effectSnowflake provides the control surface. Hive signs that the control was enforced before the action ran, in a form a third party can check.
Snowpark Container Services runs your image inside Snowflake compute You can package your application and its dependencies into an Open Container Initiative (OCI) image, which can include any programming language, framework, or library.
Provenance-Bonded Sandbox™ · continuous runtime proof

Snowflake orchestrates the container. It does not attest to a third party that the image which ran is still the image you approved. Provenance-Bonded Sandbox signs a manifest of the container, kernel, packages, ACL and GPU firmware before the work starts, then keeps a signed heartbeat while it runs, so drift has a timestamp instead of an assumption.

Cortex Guard filters unsafe model output before it reaches the application Cortex Guard, currently powered by Llama Guard 2 from Meta, works by evaluating the responses of a language model before that output is returned to the application.
Refusal Ledger™ · signed guardrail mutation chain

Cortex Guard enforces the filter. Refusal Ledger proves which version of the filter was in force at the moment of one specific decision, and that nobody widened it quietly and dated the change backward. It does this as a signed append-only chain over the policy mutations, without publishing the policy itself.

A Cortex Agent runs its own orchestration loop so you do not have to An agent reasons over a request, plans the work, calls tools, executes code, and generates a response, without requiring you to build or operate your own orchestration loop, runtime, or sandbox infrastructure.
Howler™ · drift alarm inside the reasoning loop

Not operating the loop is the product benefit, and it is also why you cannot see inside it. Howler fires a signed alarm from within that loop when the agent drifts off the task it was given, reaches for a capability it was never scoped for, or takes on context that should not be there. The alarm is a receipt, so the warning is itself evidence.

Network policies allow or deny by origin, and external access integrations open outbound paths A security administrator (or higher) can use a network policy to allow or deny access to a request based on its origin. External access integrations then let handler code inside user-defined functions and stored procedures reach specific network locations outside Snowflake.
Perimeter Bond™ · reach enforced below the application

Policy governs who may come in. Integrations open a way out from inside handler code. Perimeter Bond binds the permitted reach underneath the application and signs every refused attempt together with the exact bytecode that judged it, so the answer to whether an agent ever touched an unapproved host does not depend on the agent’s own account of itself.

Tasks run on a schedule, including when nobody is watching Tasks can run at scheduled times or can be triggered by events, such as when new data arrives in a stream. Any third-party service that can authenticate into the account and authorize SQL actions can run tasks with the EXECUTE TASK command.
Diurnal Bond™ · oversight-aware attestation threshold

Scheduled and externally triggered work runs in exactly the windows where the fewest people are looking. Diurnal Bond declares the risk regime in advance and signs it, then raises the number of independent attestations required before an action may run once the clock crosses into a low-oversight window. Fewer eyes means more proof.

Secure Data Sharing exposes objects to other accounts, and bulk unload writes data to files Secure Data Sharing lets you share selected objects in a database in your account with other Snowflake accounts. Bulk unload separately exports data from a table into flat delimited text files.
Egress Bond™ · pre-committed caps by semantic class

Sharing decides who may read. Unloading moves bytes out of the account. Egress Bond commits, before the run starts, to a cap on what may leave by class of data, then signs the measurement against that commitment. A breach names the class that broke it and the run can be invalidated after the fact, which is a control rather than a subsequent discovery.

Access History reports what data was accessed and how it moved The ACCESS_HISTORY view provides a unified picture of what data was accessed, when the data access took place, and how the accessed data moved from the data source object to the data target object. Time Travel separately allows access to historical data within a defined retention period.
Forensic Rail™ · bonded incident access and replayable analysis

Access History is the platform’s account of its own access, read with platform privileges by whoever holds them. Forensic Rail issues a bonded credential that requires several independent approvers, bounds the session so that looking cannot turn into acting, and makes the analysis replay byte for byte. The investigation becomes an exhibit instead of a claim.

The seven do not report to a dashboard. They report to a gate. A single upstream gate refuses to let an action proceed unless every receipt it requires verifies and is fresh, so a missing proof is a refusal rather than a warning. Fifteen receipt types sit behind the seven and every one of them is live and keyless today, signable from a browser in the Hive receipts catalogue. Two of the seven, Perimeter Bond and Egress Bond, enforce inside the runtime where the agent executes, so standing those up in a customer environment is integration work rather than a setting. Primitives marked ◇ are patent pending. Hive does not operate, replace or sit in front of Snowflake governance, and a signed record that a rule ran is not a statement of legal, regulatory or compliance status.

06
Proof demonstration

Load, verify, alter, restore, and download the proof record in the page.

This illustrative Snowflake workflow uses one governed dataset, one Slack summary, and one Jira ticket. The verifier is bundled in the page, works after load with no login, and makes no post-load network call.
Illustrative Snowflake workflow

One governed action. One proof file. One later answer Maya can verify.

A Snowflake CoWork pricing review agent reads regulated customer pricing records, prepares a Slack summary for the pricing governance channel, and opens a Jira ticket for manual review. Hive does not replace the workflow. Hive adds the proof record at the decisive moment.

Governed dataset FIN.REGULATED_CUSTOMER_PRICING under row policy us-bank-regulated-v4.
Authority and rule pricing-servicing-v12 allows the summary and Jira escalation for approved reviewers only.
Slack delivery One summary to #pricing-governance for the review team.
Jira delivery Ticket GOV-2418 opens the manual review path.
Production rail

The verifier above runs locally. This one calls the live signing rail.

Live endpoint

The demonstration above is self-contained so it keeps working with the network off. This panel is the opposite. It calls receipts.thehiveryiq.com and returns a freshly signed receipt from the production signer: an ML-DSA-65 post-quantum signature under NIST FIPS 204, co-signed with Ed25519, plus the signer timings measured on that call. Nothing here is pre-recorded, and no Snowflake or customer data is involved.

Open the public verifier
ML-DSA-65 signature bytes
Public key bytes
Signer time on this call
Browser round trip
Idle. No call has been made yet.

The receipt records that a signing action occurred on this rail. It is not a statement of any customer relationship, engagement or endorsement, and it says nothing about Snowflake. Signer time is measured inside the signer and reported by it. Browser round trip includes network and TLS time and will always be larger. The ML-DSA-65 signature is 3,309 bytes and the public key is 1,952 bytes, both fixed by FIPS 204.

07
The same question, asked twice

Fourteen months later, Maya either reconstructs or verifies.

This comparison is clearly illustrative. It does not claim to reproduce a live Snowflake query. The local verification on the right is real and uses the same verifier bundled in the page.
Retention timeline

Drag the day. Two different limits arrive at two different times.

The first limit is on the calendar and it is easy to see coming. The second limit was there on day zero and never moves. Snowflake keeps working correctly throughout. Nothing below is a defect.

Day 0 the day the agent ran
Day 0 Day 365window edge Day 425
Snowflake platform record Current

ACCESS_HISTORY is populating, with up to 180 minutes of documented latency. Horizon Catalog carries the lineage. Everything an operator needs to answer the question is in place.

source · ACCOUNT_USAGE · retention 365 days
Hive signed receipt Verifies

Canonical bytes over RFC 8785 JCS, a SHA-256 payload hash, an Ed25519 signature and an ML-DSA-65 cosignature, against a published public key. It checks offline with no call back to Hive.

retention · held by whoever holds the file · unchanged by the calendar
The limit that does not depend on the clock

This limit was true on day zero. Inside the window or outside it, the platform’s account of its own behaviour is the one form of evidence a reviewer is trained not to accept on its own. The calendar only decides how hard the answer is to assemble. It was never the reason someone outside wanted an independent record.

Illustrative comparison

Once the event is fourteen months old, the difference is evidentiary posture.

The first answer is spread across Snowflake, Slack, Jira, and time windows. The second answer is one proof lookup.

Ordinary platform lookup

Useful record, incomplete answer

The point is not that Snowflake has no logs. The point is that Maya still has to assemble the answer from different systems after the ordinary one-year platform window has passed.

  • Question 1: who authorized the agent?
  • Question 2: which rule allowed it?
  • Question 3: what data did it read?
  • Question 4: where did the information go?
Independent proof lookup

Found and verifiable

The proof record is illustrative. The verification is real. The reviewer gets one portable answer instead of a cross-system reconstruction.

  • Authority grant captured
  • Policy version captured
  • Data read captured
  • Slack and Jira delivery captured
08
Pilot roadmap

Start with one agent, one governed dataset, and one downstream system.

The pilot is not a platform rewrite. Keep Snowflake as the operator. Add one independent proof record for one governed workflow where Maya is likely to hear the same question again.
Phase 1

Prove the narrow workflow

One Snowflake agent, one governed dataset, one downstream system, and one question Maya can answer from one verifiable record.

Phase 2

Add a second handoff

Extend the same record shape to one more downstream action or approval step without changing the proof model.

Phase 3

Repeat on the next regulated workflow

Once the pattern is stable, move to the next agentic workflow where the same audit question will appear.

Pilot builder

Generate a concise pilot scope

Choose one Snowflake agent, one governed dataset, and one downstream system. The page will generate a compact pilot brief that stays inside those boundaries.

Pilot summary

One narrow workflow, clearly bounded

Agent
Dataset
Downstream

    09
    Decision close

    Eight buyer points lead to one standard.

    These are the same buyer points in the brief, expressed as an executive sequence instead of a dashboard wall. The final standard is simple: if the question matters, another party has to be able to verify the answer.
    • 01

      Snowflake already governs your data well.

      That is the starting point, not a concession Hive has to fight.

    • 02

      Intent is becoming action.

      Snowflake is turning governed context into work across enterprise systems.

    • 03

      The record stops at the edge, and expires.

      Snowflake documents the time window and the exclusions. Slack and Jira add more system boundaries.

    • 04

      Same platform. A record anyone can check.

      Hive adds a second record without asking Snowflake to stop being the platform.

    • 05

      Four layers, clearly divided.

      Authority, identity, action, and outside verification each have their own role.

    • 06

      Answers in minutes, not reconstructions.

      Maya should be looking up fields, not stitching a story together under time pressure.

    • 07

      Authority, action, proof, review, repeat.

      That is the loop a regulated buyer can understand without learning new jargon first.

    • 08

      The same question, asked twice.

      The first answer is a reconstruction. The second answer is a proof lookup.

    09

    Verifiable trust is the only kind that is defensible.

    Snowflake governance matters. So does the fact that another party can verify what happened without trusting Snowflake alone. That is where Hive belongs: beside Snowflake, at the point where the answer has to survive outside review.

    10
    Official Snowflake source set

    Only Snowflake's own materials are cited here.

    The goal is buyer relevance and accuracy. These are the official Snowflake sources behind the control-plane framing, governance context, identity direction, and documented audit-record limits used on this page.
    Control plane direction

    Agentic work and Snowflake CoWork

    Snowflake frames the platform as the control plane for the agentic enterprise and describes CoWork as a work surface for connected action across enterprise tools.

    Governance context

    Horizon Catalog and trusted AI posture

    Snowflake describes Horizon Catalog as a trust layer for enterprise AI and a governance control plane across data inside and outside Snowflake.

    Identity and detections

    SERVICE_AGENT and Trust Center

    Snowflake has taken the SERVICE_AGENT user type to GA and separately shipped Trust Center detections and event-driven scanners to general availability.

    Agent surface quoted in section 04

    Cortex Agents and Horizon Catalog

    Every quotation in the correlation section is taken verbatim from these two documents, covering the agent reasoning loop, the full tool set including the code sandbox, MCP connectors and web search, threads, and the Horizon governance surface.

    Surfaces quoted in section 05

    Shared responsibility, containers, guardrails, network, tasks, sharing and access history

    Every left-column quote in the pre-effect chapter comes from these official Snowflake pages, including Snowflake’s own statement of the shared responsibility model.

    Audit record limits

    Account Usage and ACCESS_HISTORY

    Snowflake documents one year of Account Usage history, up to 180 minutes of ACCESS_HISTORY latency, and a published set of exclusions and truncation behavior.

    new in the canon ยท runnable on this page

    Carry a comparison beyond the platform

    This newer receipt preserves a comparison between the platform record and the downstream acknowledgement Maya must later explain. It has been completed in code, remains undeployed, and the runs below make that clear.

    ledger.parity · Deployed in production

    Compare the platform record with downstream acknowledgement

    An outside reviewer can use this receipt when a Snowflake action and a later Slack or Jira acknowledgement need to be compared. It pins each named record to its own cursor, time, attestor key, and fingerprint over the declared fields. The comparison result is recalculated against a stated time tolerance instead of taken from either system. That gives Maya a compact answer about whether the selected records agree without exposing the underlying customer data.

    What it does not do. It does not disclose the customer record, account identity, or any position or balance. It cannot confirm either system made a correct record, choose a correct side after a difference, assign responsibility, judge an underlying transfer, register update, or settlement, or alter a delivery, ticket, or settlement; records observed too far apart yield no decisive comparison.

    POST /verify/ledger-parity · case pass, a clean record

    Nothing has run yet. Click Run it and the answer below comes back from the verifier, not from this page.

    POST /verify/ledger-parity · case diverge, the two records disagree

    Nothing has run yet. Click Run it and the answer below comes back from the verifier, not from this page.

    POST /verify/ledger-parity · case fail, a forged record

    Nothing has run yet. Click Run it and the answer below comes back from the verifier, not from this page.

    Every run above posts a verified request body from this domain to the open verify route and prints what came back. The example receipts are signed with published example keys, so verify reports key_trust example_registry. That is on purpose. Nothing on this page is a production issuance, a customer record, or an endorsement. Patent Pending.