Client-controlled AI for regulated operations

Run AI workflows inside boundaries your team can inspect.

DecarbDesk installs private AI infrastructure, connects it to operational systems, and defines the approvals, evaluations, and audit records required for production use.

Review our services Review assurance

A governed execution trace

A workflow does not act on a model response alone.

See reliability and DSPy evaluation

01
Source

Authorized records and documents
02
Policy gate

Role, scope, and data checks
03
AI operation

Extract, classify, draft, or route
04
Evaluation

Versioned tests and quality thresholds
05
Human review

Approval when risk or uncertainty requires it
06
Audit record

Inputs, outputs, scores, and decisions

Infrastructure and operating controls belong in one scope.

A private model endpoint is not a production service on its own. The workflow also needs authorized data access, deterministic routing, review rules, evaluation, monitoring, and a clear handover.

Infrastructure Sovereign AI infrastructure Private inference, secure connectors, workflow orchestration, deployment, and managed operations in a client-controlled environment. Governed delivery Controls, evaluation, and handover Use-case assessment, oversight design, approval logic, evaluation sets, operating documentation, and reviewer training. Start here Workflow assessment Map one process, identify its constraints, and decide whether automation is worth pursuing before committing to a build.

Example workflows

See what the system does and where a person decides.

These patterns show the division of work inside a governed workflow: automated system actions, explicit review points, and records that explain what happened.

Finance workflow

Collections Coordinator

Reviews open invoices on a set schedule, prepares follow-ups, and updates the cash forecast from approved accounting data.

System actions: Daily scan of all open invoices in your accounting software
Sorts receivables into aging buckets (0-30, 31-60, 61-90, 90+ days)
Drafts personalized follow-up emails based on aging and customer history
Nets credit memos before flagging invoices as overdue
Updates the rolling 13-week cash forecast from current receivables data
Human decision: Collection emails above your dollar threshold; controller approves in your team chat
Disputed invoices: pauses automation and routes to your accounts receivable team
Recorded outputs: Daily collection emails on a configurable cadence
Rolling 13-week cash forecast posted to your team channel every Monday
Exception alerts for bounced emails, duplicate invoices, and disputes

Current manual work: Manual invoice review, follow-up drafting, aging summaries, and recurring spreadsheet forecast updates.

Finance workflow

Reconciliation Clerk

Compares bank transactions with accounting entries and routes unresolved differences to a reviewer.

System actions: Daily sync of bank feed entries and accounting transactions
Proposes matches by amount, date, and reference number, with confidence scores
Flags unmatched items with suggested matches and confidence scores
Detects duplicate bank entries and unusually large transactions
Compiles weekly income, expenses, cash position, and receivables/payables summary
Human decision: Unmatched transactions; bookkeeper reviews exceptions in a review queue
Adjustments posted back to your accounting system after manual resolution
Recorded outputs: Weekly financial summary posted to your leadership channel every Friday at 9 AM
Executive summary emailed to your distribution list
Exceptions sheet with suggested matches for quick resolution

Current manual work: Manual transaction matching, exception-list preparation, and recurring financial-summary assembly.

Finance workflow

Document Processor

Extracts structured fields from financial documents, validates totals, and prepares entries for bookkeeper review.

System actions: Detects and classifies incoming documents (vendor invoice, bank statement, expense report)
Extracts structured fields: vendor, invoice number, date, line items, amounts, total
Cross-checks totals against line item sums and flags mismatches
Detects duplicate invoice numbers against existing records
Archives processed documents to your file storage with a processing log
Human decision: Every extraction reviewed by bookkeeper before posting to your accounting system
Unrecognized vendors require manual confirmation before creating a new record
Recorded outputs: Pre-filled data summaries for side-by-side verification
Approved entries posted to your accounting system as bills or expenses
Processing tracker with document history and status

Current manual work: Manual field entry, duplicate checks, total validation, and document-status tracking.

Operations workflow

Intake Dispatcher

Checks inbound requests for required information, applies routing rules, and sends exceptions to an operations reviewer.

System actions: Captures requests from your web forms and intake inbox
Validates required fields and auto-requests missing information
Categorizes by service type, urgency, and region
Routes to the correct team member based on capacity and rules
Detects and quarantines spam submissions
Human decision: High-value or high-complexity requests; ops manager reviews in your team chat
Reassignment when no team member is available in the assigned region
Recorded outputs: Confirmation email to the requester with tracked status
Live dispatch board with assignee, status, and timestamps
Escalation alerts when submitters do not respond within 48 hours

Current manual work: Manual inbox review, request categorization, assignment, and dispatch-tracker updates.

Operations workflow

Reporting Analyst

Combines approved operational sources, flags defined anomalies, and prepares a recurring management summary.

System actions: Daily 6 AM data pull from your accounting, CRM, and operational tools
Normalizes date formats, currency values, and metric definitions across sources
Flags metrics deviating 15%+ from trailing 4-week average
Checks anomalies against same-period-last-year for seasonal context
Populates your dashboard with current values and trend lines
Human decision: Anomaly flags reviewed by ops manager before the summary publishes
New metrics added from source tools; queued for template update review
Recorded outputs: Monday 8 AM executive summary in your team channel and email with wins, risks, and action items
Live KPI dashboard with filtered views per department
Anomaly alerts with context and trailing comparison data

Current manual work: Manual data pulls, format normalization, anomaly checks, and recurring report assembly.

Support workflow

Support Triage Lead

Classifies inbound tickets, retrieves approved support material, and prepares a response for review.

System actions: Parses incoming emails and support tickets for issue type, product, and urgency
Searches documentation, past responses, and FAQ entries for relevant answers
Drafts a first response tailored to the specific request
Links customer replies to existing threads instead of creating duplicates
Filters out spam, vendor pitches, and non-support messages
Human decision: Every draft response; your team reviews before it sends
Sensitive data detected (credit card, SSN patterns): routed for manual handling
Recorded outputs: Draft responses ready for one-click approval
Tracking dashboard: open tickets, response time, top categories
Weekly support summary with volume, resolution time, and trending issues

Current manual work: Manual ticket categorization, knowledge-base lookup, and first-response drafting.

RevOps workflow

Follow-Up Coordinator

Prepares follow-up messages, applies lead-routing rules, and assembles context for sales review.

System actions: Enriches new contacts with company size, industry, and source channel from your CRM
Scores and segments leads based on fit signals and engagement
Drafts personalized first follow-up based on source and expressed interest
Runs multi-step nurture sequences on a configured cadence
Tracks opens, clicks, and replies to update lead scores in real time
Human decision: Leads above the MQL threshold; sales lead reviews and approves the response
Named-account leads: bypass nurture and route directly to sales with full context
Recorded outputs: Personalized follow-up email on the configured cadence
MQL handoff notification with source, engagement history, and recommended next step
Engagement dashboard: leads by source, conversion funnel, reply rates

Current manual work: Manual contact enrichment, follow-up drafting, lead scoring, and sales-handoff preparation.

RevOps workflow

Pipeline Analyst

Applies agreed deal-health rules, identifies stalled records, and prepares a pipeline summary for manager review.

System actions: Daily sync of active deals, contacts, and activity history from your CRM
Scores each deal on stage velocity, last activity, email response rate, and next steps
Flags deals below health threshold or with no activity in 7+ days
Groups closed-lost deals by reason category to identify recurring patterns
Compiles weekly pipeline report with health scores and trend data
Human decision: Pipeline digest reviewed by sales manager before it publishes to the team
At-risk deal alerts sent to reps only after manager confirms the flags
Recorded outputs: Monday 8 AM pipeline digest with deal health scores, risk flags, and stage movement
Stalled-deal alerts after the manager-approved inactivity threshold
Weekly closed-lost pattern analysis with specific deal examples

Current manual work: Manual pipeline extraction, health scoring, stalled-deal review, and weekly digest assembly.

Connects to the systems already in use

Gmail

Outlook

Google Sheets

Excel

QuickBooks

HubSpot

Salesforce

Slack

Teams

Stripe

Shopify

Yelp

Zendesk

SharePoint

Google Drive

Notion

Google Docs

Dropbox

Discord

X / Twitter

Chrome

Obsidian

Ollama

+ more

One delivery sequence from workflow map to handover.

Infrastructure and assurance move through the same delivery process. Controls are designed before deployment and checked again during operation.

Review the full delivery model →

01
Discover

Map the workflow, systems, stakeholders, and operating constraints.
02
Assess

Test suitability, risk, oversight needs, and evidence gaps.
03
Design

Define integrations, access, approvals, audit fields, and data contracts.
04
Deploy

Run reference cases, test exceptions, and release with monitoring in place.
05
Govern

Review evaluation scores, regressions, exceptions, and control changes. See evaluation →
06
Handover

Train operators and reviewers, document administration, and transfer the system.

Review the controls before you review the demo.

Each assurance area explains what is checked, what is recorded, and where a person remains responsible.

Reliability & evaluation

Versioned evaluation sets, DSPy-based optimization, quality thresholds, and deployment gates.

Review this area →

Security & controls

Access boundaries, human approvals, audit records, exception handling, and stop controls.

Review this area →

Responsible AI

Use-case assessment, human oversight, impact readiness, documentation, and operator training.

Review this area →

Know where data is processed and who operates each layer.

We size the deployment around the workflow, data sensitivity, integration surface, and expected load. The implementation record names each component and its operating owner.

Review security boundaries →

03

Application boundary

FastAPI service layer

Typed interfaces, authenticated routes, workflow orchestration, and documented APIs.
02

Inference boundary

Local model serving

Model execution inside the client environment, with hardware acceleration where available.
01

Compute boundary

Dedicated AI hardware

Client-controlled compute sized to the workload, concurrency target, and data boundary.

Client-controlled: deployment boundary
Role-based: operator and reviewer access
Documented: interfaces and handover

What teams ask before discovery.

Do we need technical staff to operate the system?

No. We install the system, connect it to your tools, document its controls, and train the people who will operate and review it. Ongoing monitoring and maintenance are available through an operations plan.

What happens if we cancel the operations plan?

The installed system remains in your environment. The plan covers monitoring, patching, incident support, and continued evaluation; cancelling ends that support rather than removing the system.

How is this different from an AI SaaS platform?

A SaaS platform runs the service and defines its operating boundary. DecarbDesk installs the workflow in a client-controlled environment, documents the implementation, and hands over the operating artifacts.

Can the system expand after launch?

Yes. New workflows, integrations, and reviewer roles can be added to the environment already in place. We scope each expansion against the same security, evaluation, and approval requirements.

How long does delivery take?

A workflow with clean APIs and clear approval rules can move from discovery to production testing in days. Legacy systems, fragmented data, or complex review requirements need a longer discovery and integration phase.

Bring one workflow and the question you need answered.

Email us a short description, or use the project intake form when you are ready to share the systems, review points, and operating constraints involved.

Email the desk Send project details

Run AI workflows inside boundaries your team can inspect.

A workflow does not act on a model response alone.

Source

Policy gate

AI operation

Evaluation

Human review

Audit record

Infrastructure and operating controls belong in one scope.

See what the system does and where a person decides.

Collections Coordinator

Reconciliation Clerk

Document Processor

Intake Dispatcher

Reporting Analyst

Support Triage Lead

Follow-Up Coordinator

Pipeline Analyst

One delivery sequence from workflow map to handover.

Discover

Assess

Design

Deploy

Govern

Handover

Review the controls before you review the demo.

Reliability & evaluation

Security & controls

Responsible AI

Know where data is processed and who operates each layer.

FastAPI service layer

Local model serving

Dedicated AI hardware

What teams ask before discovery.

Do we need technical staff to operate the system?

What happens if we cancel the operations plan?

How is this different from an AI SaaS platform?

Can the system expand after launch?

How long does delivery take?

Bring one workflow and the question you need answered.