Artificl Enterprise

AI that behaves like software.

Predictable, testable, auditable. Your people already have an assistant — Copilot, ChatGPT, Gemini or Claude. Artificl connects it to the systems your organization actually runs on, with a scoped set of tools, a test set that proves each one behaves, approvals where a change matters, and an audit trail for everything. Per seat, with implementation done by the person who built it.

Scoped, not sprawlingEach system exposes a handful of named tools — never a raw API
Proven before go-liveEvery tool ships with a golden test set your team signs off on
Read first, write by approvalWrites are off until an owner enables them; risky ones require a human yes
Logged for the auditorWho or what asked, what it saw, when — exportable, streamable
What "as intended" means

Most enterprise AI projects fail at the seam between the model and the system. We only build the seam.

We don't sell a model, a chatbot or a new interface. We make the systems you already trust safely operable by the assistant you already pay for, and we prove it behaves before anyone in your organization depends on it.

Scoped tool surfaces

For each system — Salesforce, ServiceNow, SAP, a DMS, a policy admin platform — we define the six to twelve questions and actions your teams actually need, and expose only those. The assistant can't wander.

A test set, not a demo

Before go-live every tool is run against a golden set of real-shaped cases your team wrote. Pass rates are reported, regressions are caught on every change, and the results are yours to keep.

Approvals where they belong

Lookups are read-only by default. Actions that change a record go through a per-system policy: allowed, allowed with a human confirmation, or off. Policies are owned by your admins, not by us.

An audit trail you can hand over

Every call — human or assistant — is logged with identity, tool, inputs and timestamp. Export it as CSV, pull it by API, or stream it to your SIEM. Retention is set by you.

Your identity, your controls

Sign-in through your identity provider (SAML or OIDC), user lifecycle through SCIM, role-based access per system, and connections that use OAuth 2.1 so no one pastes a password into a chat box.

Any assistant, and no assistant

Built on MCP, the open standard the major assistants use, so switching from Copilot to Claude or Gemini is configuration. Every board also works as a normal web app for people who don't use an assistant.

Industry packs

Start with a pack built for your industry, or bring your own job.

A pack is a pre-built board plus the tool surface and test set for it. It's the fastest way to a first live use case; the platform underneath is the same for every industry.

How an implementation runs

Four phases. You see working tools at the end of week one.

Discover

A half-day workshop with the people who will ask the questions. We leave with the system list, the questions, the write policy and the first golden test cases.

Connect

SSO and SCIM against your identity provider, then the first system's tool surface, built read-only and tested against your cases.

Prove

Your team runs the test set and real questions in a pilot group. Pass rates, latency and every call are reported. Writes are enabled only where you sign off.

Roll out

Seats are provisioned through SCIM, training runs per team, and hypercare covers the first weeks with a named engineer — the same one who built it.

Per-seat pricing

Priced per person who connects an assistant. Everything else is the platform fee.

TierNamed seatsPer seat / monthPlatform fee / yearIncludes
Team25–99$15$6,0001 system connected · SSO · read-only tools · audit log · email support
Business100–499$12$15,000Up to 5 systems · SCIM · approval workflows · audit export (CSV/API) · 99.9% uptime commitment
Enterprise500+$9 and down$30,000+Unlimited systems · SIEM streaming · DPA and MSA redlines · P1 response within 1 hour · custom retention

A seat is a named person whose AI assistant is allowed to reach your systems through Artificl. Billed annually. Two-year terms take 10% off, three-year 15%. SSO, SCIM and audit export are never gated to a higher tier — they are the product. Example: 100 seats on Business is $29,400 a year; 1,000 seats on Enterprise starts at $138,000.

Implementation packages

Fixed-fee, scoped, and led by the founder.

PackageFixed feeWhat's in it
Launch$7,500Discovery workshop · one system connected · SSO · tool scope and golden test set · two training sessions · two weeks of hypercare
Standard$20,000Launch, plus SCIM · two more integrations (ServiceNow, Salesforce, ITSM, HRIS) · historical import · approval policies · user acceptance testing
Enterprisefrom $45,000Standard, plus multi-system and multi-region roll-out · SIEM streaming · change-freeze playbook · four weeks of hypercare · executive readout
Engineering blocks40 h $8,000 · 80 h $15,200 · 120 h $21,600Prepaid hours for integration work beyond a package, at $200 / $190 / $180 an hour

Implementation is sold on an order form alongside the subscription and typically lands at 15–25% of first-year fees. Work is led by the founder; roll-outs larger than one person can deliver are staffed with contract engineers under Artificl's direction, and you're told that up front.

For procurement and security

What we bring to the review, and what we don't have yet.

Contract stack

MSA, order form, data processing agreement with sub-processor list, SLA exhibit (99.9% uptime commitment with service credits), and a statement of work for implementation. Liability caps and redlines are negotiated at Enterprise tier.

Security review

Plain-English security page, completed SIG Lite or CAIQ questionnaire on request, encryption in transit and at rest on Google Cloud, 72-hour breach notice. SOC 2 is planned, not held — we say so before you ask.

Insurance and support

Cyber liability and technology E&O coverage sized to the engagement, general liability on request. Support: P1 within one hour, P2 within four, P3 next business day, with a named engineer who knows your deployment.

Bring one system and one team.

Discovery is a half-day. You'll see your own questions answered from your own data by the end of week one.