Honto — the enterprise second brain

v.26 / EN · ES

From static knowledgeto scaledexecution.

Honto captures your company's expertise — decisions, heuristics, standards — and puts it to work as AI agents. What used to live in docs, silos, and people's heads now runs across every team.

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[01] Production-proven[02] Audited & traceable[03] Domain-native

Palo Alto, CA

Knowledge capture · Autonomous agents · Retrieval pipelines · DevSecOps for AI · Model evaluation · Domain skills · Decision support · Observability · Safe rolloutsKnowledge capture · Autonomous agents · Retrieval pipelines · DevSecOps for AI · Model evaluation · Domain skills · Decision support · Observability · Safe rolloutsKnowledge capture · Autonomous agents · Retrieval pipelines · DevSecOps for AI · Model evaluation · Domain skills · Decision support · Observability · Safe rolloutsKnowledge capture · Autonomous agents · Retrieval pipelines · DevSecOps for AI · Model evaluation · Domain skills · Decision support · Observability · Safe rollouts

[01] Problems we solve

Six signs your AI strategy is not the right one.

P.01

Your people use AI every day. Your company still works the old way.

Individual productivity isn't an operating model. We identify the workflows where AI rewrites the dynamic of your business and build the systems that make the shift real.

P.02

Your senior experts are still the bottleneck.The tools don't know what they know.

We extract the judgement your experts carry — standards, heuristics, edge cases — and encode it into AI skills the rest of the team can consult without interrupting them.

P.03

Your data lives in fifteen systems. Only a few are available to the AI.

We build the connective layer — adapters, extractors, and retrieval — that lets AI reason across your IoT platforms, ERPs, design files, and PDFs. From oilfield telemetry to accounting ledgers, every source becomes a first-class input to your business intelligence.

P.04

Generic models give confident answers that are wrong for your business.

Grounded in your documents, your data, your decisions. The system cites its sources, refuses when it shouldn't guess, and defers to the people who should decide.

P.05

Legal and risk said no to the interesting use cases.

Every prompt, retrieval, and tool call is traced and policy-checked in-line. Exportable audit trails for SOC 2, HIPAA, the EU AI Act — whatever you're accountable to.

P.06

You need an AI operating model, not another license.

Architecture, team shape, data contracts, review loops. We build it with your engineers so that when we leave, the method — not just the system — stays.

[02] Method

From expert judgment to production system, in four deliberate phases.

Phase / Discovery

Map

We sit with your experts, shadow workflows, and surface the 20% of decisions that move 80% of outcomes.

Phase / Engineering

Build

Architecture, skills, retrieval, evals. Every component version-controlled, documented, and reviewed like critical infrastructure.

Phase / Rollout

Deploy

Shadow-mode → assisted → autonomous, with guardrails and rollback. Observability, SLOs, and audit trails live from day one.

Phase / Continuous

Operate

We stay on as the SRE layer for your AI — evals on every change, drift monitoring, upgrades, and the runbooks your team owns.

[03] Capabilities

A full stack. One team. No handoffs.

C.01

AI Strategy

An assessment of where AI creates real leverage in your ops — and a 90-day plan to get there, not a 200-slide deck.

RoadmapROI modelRisk register

C.02

Autonomous Agents

Multi-step workers that read your systems, make bounded decisions, and hand off to humans when they hit the edge of their authority.

Tool useGuardrailsHandoff protocols

C.03

Domain Skills

Reusable AI modules encoded with your methodologies — a skill for cost estimation, another for code review, another for compliance triage.

Skill registryVersioned promptsEvals

C.04

RAG & Knowledge

Retrieval grounded in your real artifacts — code, specs, Slack, Confluence, the 800 PDFs nobody opens — with citations on every answer.

Hybrid retrievalRerankingGrounding evals

C.05

AI Infrastructure

Serving, queues, vector stores, secrets. Kubernetes or serverless, your cloud, your compliance posture. No vendor lock.

TerraformObservabilitySOC2-ready

C.06

Evals & Ops

The part most teams skip: a test harness that catches regressions before your users do. We run it on every change.

Golden setsLLM-as-judgeDrift monitors

[04] Product · honto.ops

The expert second brain for your engineering org.

honto.ops watches your systems, reads your docs, and answers the questions your senior engineers field fifty times a week — with the same judgment, at 2am, in every timezone.

Capture

Every decision, indexed.

Scale

One expert, whole org.

Ground

Cites every answer.

Audit

Logged, replayable.

Explore honto.ops

[05] Principles

Six commitments. Non-negotiable.

P.01

Engineering, not prompting.

Version-controlled, reviewed, tested. We treat AI systems like any critical service — because they are.

P.02

Grounded or silent.

If the system isn't sure, it says so. If it can't cite, it refuses. We engineer for calibrated answers, not confident ones.

P.03

Traceable by default.

Every prompt, retrieval, tool call, and decision is logged. Exportable for any audit.

P.04

Your data, your cloud.

We deploy into your environment. Your secrets stay where they are. No vendor lock-in.

P.05

Production or don't ship.

We don't do demos. First milestone is a system serving real traffic with SLOs attached.

P.06

Handoff is part of the build.

Every engagement ends with your team owning what we built — docs, runbooks, on-call trained.

[06] Contact

Tell us about
the problem.

Emailinfo@honto.ai

Response< 24 hours

RoutingStraight to engineering

NDAOn request · same day

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