KLA Digital — Mission & Vision Document

A living charter for engineers, designers, and go-to-market teams building the audit-grade Agent Ops platform.

1. Why We Exist

Mission > “Turn every AI decision into provable evidence and every risky outcome into a preventable event.”

Modern enterprises can no longer separate building AI from governing it. Regulations (EU AI Act, HIPAA, MiFID II, NIST RMF) demand immutable records, human oversight, and continuous risk management. Yet most LLMOps tools stop at developer observability—logs that can be altered, alerts that fire after harm occurs, and quality metrics that live outside compliance workflows.

KLA Digital flips the stack: we treat AI traffic as regulated evidence first, engineering telemetry second. Our platform records, enforces, and audits agent behaviour in real time so that developers move fast, while risk officers sleep at night.

2. What We Aspire To Become

Vision > “The globally trusted control-plane that lets every regulated organisation deploy autonomous agents without sacrificing accountability.”

  • Five years out, when a bank, hospital, or defence agency asks, “How do we prove our AI did the right thing?”—the default answer will be “It’s in KLA.”
  • A mature ecosystem of evaluation, RLHF, and APM tools will feed into—and draw from—our immutable ledger, but governance authority will remain here.
  • Front-line humans (nurses, compliance officers, call-centre managers) will supervise AI through KLA’s gatekeeper console, not obscure YAML or code reviews.
  • Regulators will cite KLA audit exports as reference examples of best-practice transparency.

3. Core Differentiators (Non-Negotiables)

  1. Tamper-Proof Audit Ledger

  2. Hash-chained, append-only records anchored to external timestamping.

  3. Seven-year+ retention with WORM (write-once-read-many) object storage.

  4. Self-service data-room exports for regulators or legal discovery.

  5. Real-Time Human Gatekeeping

  6. Policy-driven “pause-points” that block an agent mid-flight.

  7. Approve / Reject / Rewrite workflows logged with reviewer identity.

  8. SLA clocks and escalation paths to guarantee business continuity.

  9. Policy-as-Code Governance Engine

  10. Declarative rules (risk-score, PII detection, role constraints) signed and versioned.

  11. Enforcement spans: request time, runtime, and deployment admission.

  12. Single source of truth for RBAC/ABAC across UI, API, and infra layers.

  13. Zero-Trust Execution & Provenance

  14. SPIFFE identities + mTLS for every micro-service hop (road-mapped).

  15. Least-privilege scopes in agent manifests; no silent tool creep.

  16. End-to-end caller chain embedded in OpenTelemetry spans.

  17. Developer Velocity Without Compliance Drift

  18. One-file agent manifests; hot-reload canary roll-outs.

  19. Automatic evaluation hooks (RAGAS, TruLens, DeepEval) for quality SLOs.
  20. “Promote to prod” requires gated policy tests—no shadow deployments.

4. Operating Principles

  • Evidence over Hunches – Every system decision must be reconstructable from ledger data; “we think it happened” is failure.
  • Stop > Alert – Prevent damage first, notify second. A gate that halts a rogue output is worth ten dashboards.
  • Least Ceremony, Maximum Provability – Default UX is a single click or single YAML line; behind the scenes, cryptography and policy engines do the heavy lift.
  • Open, Pluggable, Uncompromising – Integrate freely (OpenTelemetry, LangChain, Datadog, HumanLoop, Scale AI) but never weaken core guarantees.
  • Shared Language for Dev & Risk – Screens show audit hashes and latency graphs side-by-side; no caste system of “engineering tools” versus “compliance portals.”

5. MVP Scope (End of Q3 2025) — The “Thin Slice of Truth”

  • Runtime: single chat-agent kernel (OpenAI GPT-4o) with llm_generate + rag_search steps.
  • Immutable Ledger: immudb + hourly OpenTimestamps anchoring.
  • Policy Engine: Cerbos for RBAC & two starter rules (high-value advice gate, regex-based PII mask).
  • Human Gatekeeper UI: Next.js inbox for pending approvals with Approve / Rewrite actions.
  • Auth: Keycloak OIDC, realm-per-tenant, Postgres RLS isolation.
  • Observability: basic OpenTelemetry spans → Jaeger; latency & token metrics → Prometheus + Grafana.
  • DevOps: GitHub Actions → cosign → ArgoCD → EKS (single EU region).
  • Demo Script: regulated finance chatbot, policy trigger, human rewrite, ledger proof export.

If an auditor, CISO, and prompt engineer can each complete their critical tasks inside this slice, we ship.

6. North-Star Metrics

  1. Evidence Integrity: percentage of ledger entries anchored externally within < 60 min (target 99.9 %).
  2. Gate Response Time: median time from pause to human decision (target < 30 s for high-priority queues).
  3. Policy Drift: number of production agent actions executed under an out-of-date policy hash (target = 0).
  4. Developer Cycle Time: mean duration from manifest commit to canary traffic (target < 10 min).
  5. Audit Prep Effort: engineer hours to produce a regulator-ready evidence zip (target ≤ 1 hr, stretch = 1 click).

7. Product & Engineering Roadmap Themes (Post-MVP)

  • Ecosystem Connectors – bidirectional data pipelines to Datadog, New Relic, HoneyHive, HumanLoop, etc.
  • Multi-Model Orchestration – Anthropic, open-source LLMs, and model routing under the same governance.
  • Service-Mesh Identity – SPIRE-issued workload certs, mandatory mTLS, zero-trust perimeter.
  • Advanced Evaluations – plug-in marketplace for custom metrics, automatic RLHF data export.
  • Managed Reviewer Service – on-demand trained humans for clients lacking in-house gatekeepers.
  • Multi-Region, Cross-Ledger Proofing – EU data residency plus disaster-proof audit continuity.

8. Culture & Values for the Engineering Org

  • Regulation is a Feature – We treat compliance constraints as design primitives, not after-the-fact tickets.
  • Prototype, Then Harden – Show value fast, but every MVP line of code must have a path to formal verification or deletion.
  • Cryptography, Not Trust – When forced to choose, favour mathematical guarantees over policy docs.
  • Radical Candour, Ruthless Focus – Debate fiercely, converge quickly, cut scope without mercy.
  • Dogfood Daily – Internal chatbots run on the same production cluster; engineers feel the pain before users do.

9. Success Looks Like…

  • A Tier-1 bank passes an external audit using KLA exports with zero remediation items.
  • A hospital’s oncology agent is live with human gating, and clinicians trust it enough to save 20 % report time.
  • Developers gush that adding KLA was “two YAML lines,” yet the compliance team finally sleeps.
  • Competitors reference “KLA-style immutable audit logs” in their sales decks—validation we set the standard.

10. Closing Charge

KLA Digital is not just another LLM dashboard. We are building the black-box recorder, the guard-rail system, and the compliance cockpit for the age of autonomous software. Every design decision, line of code, and GTM move must reinforce the promise: trustworthy AI, provable at any moment, stoppable at any moment.

Welcome to the mission. Let’s make regulated AI boringly safe—so innovators can be thrillingly bold.