Connect target
RAG endpoint, agent service, trace export, or RAGhelm reference architecture.
AI release control for private systems
Release evidence infrastructure for private AI systems.
Gateproof connects to a private RAG or agent target, captures release evidence, applies versioned policy, and emits a release status: ship, needs review, or block.
Category: Gateproof is the release status check for private AI systems. It makes evidence, waiver policy, and override records reproducible before production.
Release gate
Versioned evidence
Disclosure-safe proof
Backend-neutral
From candidate build to release decision.
Gateproof turns fragmented AI quality signals into a customer-controlled release status. It does not replace tracing, eval, RAG, agent, or CI tools. It makes their evidence releasable.
Capture evidence
Golden examples, traces, retrieval records, tool calls, latency, cost, stale citations, privacy checks, policies, and hashes.
Apply policy
A versioned policy runs over pinned release evidence. The model may be stochastic. The release policy is reproducible.
Emit artifacts
ReadinessScorecard, RAGRunManifest, redacted proof bundle, and override record.
Enforce gate
Humans, agents, CI, or governance workflows accept, block, or override with a customer-owned record.
The release path in one view.
Gateproof turns private AI release review into a reproducible chain of target state, evidence, policy, release status, proof artifacts, and override records.
RAG or agent target
RAG endpoint, agent service, trace export, or RAGhelm reference architecture.
Capture layer
Golden examples, traces, retrieval records, tool calls, latency, cost, stale citations, privacy checks, policies, and hashes.
Deterministic gate
Versioned thresholds, freshness rules, judge configuration, confidence thresholds, and fail-closed policy checks.
Proof bundle
Scorecard, manifest, release status, redacted failures, artifact hashes, and override policy.
CI or review gate
Ship, block, or override with an archived customer-owned decision record.
A release record, not another dashboard.
Existing tools generate evidence. Gateproof makes evidence releasable and becomes the release-system-of-record for private AI systems.
Tracing and evals
Prompts, retrieval, tools, tokens, latency, cost, quality metrics, experiments, datasets, and monitoring.
RAG and agents
Build and run RAG apps, ingestion, chat, workflows, agent services, and retrieval systems.
Generic enforcement
Tests and deployment gates that can enforce or report an AI-specific evidence contract.
AI release approval
Release status, manifest, redacted proof, waiver policy, and archived decision record.
Sample proof artifacts.
Static samples make the product tangible while keeping sensitive evidence out of the public page.
Readiness scorecardRelease status with quality, retrieval, privacy, stale-citation, latency, cost, and regression deltas.
Run manifestAudit record of target version, corpus snapshot, model, prompt, evaluator, threshold policy, and hashes.
Redacted failuresDisclosure-safe examples that explain why a release ships, needs review, blocks, or is overridden.
AI teams can build faster than platform, security, and compliance can approve.
The buyer needs one artifact that says what changed, what failed, what evidence is private, and why the release can ship or must be blocked.
✓
Corpus updates create release risk
Answers can cite stale or superseded policies when the knowledge base changes.
✓
Model and prompt changes hide regressions
Teams can cut cost while increasing unsupported claims or failures on golden examples.
✓
Agents expand the blast radius
Tool calls can drift outside approved workflows unless release evidence is reviewed.
✓
Private data needs disclosure control
Metadata and filter bugs can expose tenant-specific context. Proof bundles need redaction by design.
Beachhead, paid pilot path, and earned moat.
Start where release approval already hurts: private RAG or agent workflows moving from prototype to customer-facing or operational software.
Private-data AI teams
AI platform and security teams at B2B SaaS and regulated-data companies shipping private RAG or agent workflows over customer, account, policy, workflow, or proprietary knowledge data.
4-6 week engagement
One production or staging RAG/agent target, 30 to 100 golden examples, baseline and candidate releases, CI or reporting path, and a redacted proof bundle.
Pilot-ready product path
Release-policy engine, scorecard and manifest schemas, target adapters, private deployment path, and proof-bundle workflow.
Earned release record
Archived manifests, overrides, approvals, proof bundles, anonymized failure taxonomy, and OSS RAGhelm distribution.
$20k-$50k
Paid pilot range for four to six weeks.
$75k-$150k
Target annual private deployment range after pilot conversion.
$1.5M
Pre-seed target for 18 months to turn RAGhelm and Gateproof into a pilot-ready product.
Founder-market fit
Founder-market fit in private AI release evidence.
Gateproof is founder-led by a production software and AI systems builder with enterprise-style RAG and GraphRAG implementation experience.
Production reliability posture
Production software, AI systems, and enterprise-style RAG/GraphRAG implementations.
Revenue and validation signal
$250k in GraphRAG consulting revenue over the past year through AgentLab.us LLC and one paid-pilot conversation in progress.
Near-term focus
The next 90-day milestone is 2-3 design-partner or paid-pilot conversations, one conversion path to annual contract, and a repeatable ICP and ROI case.
Investor and design-partner access
Request the brief or discuss a pilot.
Use this form for investor diligence, design-partner conversations, or early buyer intros. The public site keeps claims tight and routes sensitive material to direct follow-up.
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