Whitepaper

The Guided Terminal

Architecture of a budget-governed, brandable AI intake system

Eudai Gestalt Integrations · workflowtech.ai · 2026 · download .md

The problem

Public AI chat widgets fail their operators in two directions at once. Left open, they burn API spend on whatever visitors type and say things the business never approved. Locked down, they become decoration: a search box that apologizes. Most teams ship one, discover both failure modes, and quietly remove it.

The terminal at workflowtech.ai is our answer, and this paper describes how it works. The same architecture runs as GestaltWorkframe, the reusable framework the terminal is built on.

Guided intake, not open chat

The terminal never starts as a blank prompt. A short structured intake — what are you hoping to accomplish, what are you building, how automated are you today, what would help right now — routes every session into one of three persona modes (service inquiry, practitioner assistance, education) before the first model call happens. The router, not the model, decides mode transitions, tool access, and escalation. Models are workers; the backend owns orchestration.

Local-first routing with operator-controlled escalation

Every turn resolves through a provider router with an ordered route table:

Local first. A self-hosted model endpoint is the primary route when it is healthy. A sub-second health gate skips it when it is not, instead of letting a dead endpoint eat the whole request timeout.
Cloud as governed escalation. Cloud routes exist behind a budget gate: per-turn, per-session, per-day, and per-month call caps, plus dollar caps that are the true ceiling. Visitors choose the question; they never choose the spend.
A key broker, not embedded keys. Model access runs through an on-host key broker fronting multiple upstream providers behind short-lived virtual keys. Rotating a provider key is a broker operation, not a code deploy.

The ledger that says no

Spend governance is only as honest as its accounting. Every successful cloud completion must report token usage the ledger can read; a completion that cannot be metered trips a persistent accounting breaker that takes every cloud route offline until an operator clears it. We have watched this breaker fire in production on a healthy response with an unreadable usage format. That is the design working: unmetered spend is treated as an outage, not a rounding error.

The public status indicator reports the same truth. “Online” is computed from whether a route can actually serve the next turn, not from whether keys are configured.

Brandable by bundle, not by fork

Deployments are configuration, not forks. A deployment bundle — brand palette, logo, identity, intake questions, personas, routing policy, copy — is a directory of YAML the framework loads at runtime. The chaos entry animation on workflowtech.ai (the ant mark that assembles from particles and converges into the terminal frame) is a framework capability any deployment can switch on with its own logo; the particle engine samples whatever mark the bundle provides.

The research-and-publish loop

The same system curates its own public material. A discovery watchlist (RSS, GitHub repositories and topics, subreddits, YouTube channels, web diffs) feeds scheduled polling; a scout scores finds; notable items flow to a public ticker, a curated every-ten-days digest, and a Git-backed public library (CODEX) that is both human-browseable and machine-readable. Featuring, curation, and newsletter queueing are explicit operator actions with audit records.

Limitations

Guided intake trades reach for control: visitors who want a free-form chatbot will not find one here, by design.
Local-first routing assumes an operator who runs local inference; without it, the system leans on capped cloud escalation and inherits provider pricing.
The accounting breaker is deliberately blunt. A single unmeterable completion halts all cloud routing until cleared — correct for spend safety, and operationally noisy under provider-format drift.
Retrieval grounding is only as good as the curated corpus behind it.

Roadmap

CLI-style terminal presentation: intake and responses as a live prompt session rather than card UI.
Completion of the framework/implementation package split (GestaltWorkframe as a pip-installable dependency).

Verification

Live terminal: workflowtech.ai/terminal · Public library: workflowtech.ai/codex

Credentials: Claude Partner Badge: Claude Code (Anthropic, via Credly); Claude Certified Architect: Professional (CCAR-P) and Foundations.

Contact: [email protected]

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