Production-grade AI automations

Scale output,
not headcount.

We ship production-grade AI automations that remove manual workflows across finance, ops, support, and revenue—measured in hours saved and headcount avoided.

Not chatbots. Deterministic workflows with guardrails, approvals, and monitoring.

Built by engineers from

TeslaMetaOpenAIAppleAWSScaleMicrosoftCapital OneGoogleNVIDIATeslaMetaOpenAIAppleAWSScaleMicrosoftCapital OneGoogleNVIDIA
Benchmarks

CEO-legible outcomes

These are benchmark ranges. In the Audit, we model your ROI using your workflow volume and stack.

See proof
Hours reclaimed
40–200 / month
Typical range for high-volume workflows.
Cycle time reduced
30–70%
Fewer handoffs and faster routing.
Error rate reduced
20–80%
Guardrails + validation + approvals.
First workflow shipped
< 30 days
From kickoff to production.
Examples

Before / after workflows

This is where the skepticism gets answered: deterministic routing, approvals for high-risk actions, and monitoring so it's safe in production.

Browse solutions
Accounts Payable (invoice → bill)
Before
  • AP inbox triage + PDF handling
  • Manual matching to PO + vendor terms
  • Approval chasing and back-and-forth
  • Posting errors and rework
After
  • Extract + validate fields and totals
  • Match to PO, detect duplicates, flag exceptions
  • Route approvals based on thresholds
  • Post to QBO/NetSuite with audit trail
See this workflow
Support (ticket triage → resolution)
Before
  • Manual categorization and prioritization
  • Repetitive lookups across tools
  • Inconsistent policy checks
  • Escalations too late
After
  • Auto-triage with SLA risk detection
  • Attach required context automatically
  • Draft resolution + quality checks
  • Approvals for refunds/account changes
See this workflow
RevOps (lead → routed → followed up)
Before
  • Leads sit unassigned or misrouted
  • Inconsistent enrichment and scoring
  • Duplicate records and stale fields
  • Follow-ups missed
After
  • Enrich and normalize fields
  • Route deterministically using rules
  • Create tasks/sequences with context
  • Monitor routing and edge cases
See this workflow
Proof

Outcomes, not promises

We report in operator language: hours saved, cycle time reduced, errors removed.

See proof
B2B SaaS$85M ARR8 weeks to production

Finance Operations Transformation

Month-end close taking 12 days with 3 FTEs dedicated to manual reconciliation and journal entries.

Close Time
12 days 3 days
75% faster
Manual Entries
2,400/month 180/month
92% reduction
FTE Reallocation
3 dedicated 0.5 oversight
2.5 FTE savings
Enterprise Software$120M ARR10 weeks to production

Revenue Operations Automation

CRM data quality at 65% accuracy. Lead routing delays averaging 4 hours. Forecasts off by 20%+.

Data Accuracy
65% 98%
33pt increase
Lead Response
4 hours 8 minutes
97% faster
Forecast Accuracy
±20% ±5%
4x improvement
Why Northstar

De-risked automation (so it doesn't break in production)

AI skepticism is rational. We design systems that are safe, observable, and boring in the best way.

Security & reliability
Not chatbots. Workflows with guardrails.
We automate real processes with explicit states, validations, and deterministic routing.
Human approvals for high-risk actions.
Configure approval thresholds so money movement and sensitive actions never happen unattended.
Monitoring, alerts, and rollback-safe writes.
You can see what happened, catch exceptions early, and revert safely when needed.
Integrate-first: works in your stack.
QuickBooks/NetSuite, HubSpot/Salesforce, Zendesk, Slack, and more.
Process

A productized path from idea → production

Clear scope, clear deliverables, and predictable timelines.

See full process
Step 1
AI Ops Audit
Workflow ROI map + prioritized backlog + 30-day plan.
Step 2
AI Ops Sprint
Ship one workflow into production with guardrails and monitoring.
Step 3
Transformation Pod
Ongoing cadence: build workflows, report outcomes, and keep systems stable.
Pricing

Reduce tire-kickers with clear ranges

Most teams start with the Audit. If you move forward, we can apply the fee toward a Sprint (confirm details during booking).

View pricing
AI Ops Audit
$5k–$12k (typical)
Clear deliverables, clear timelines, and outcomes reporting.
AI Ops Sprint
$25k–$75k (typical)
Clear deliverables, clear timelines, and outcomes reporting.
Transformation Pod
$10k–$30k / month (typical)
Clear deliverables, clear timelines, and outcomes reporting.

Book an AI Ops Audit

We'll map workflows, quantify ROI, and ship a 30-day plan. If there's no clear opportunity, we'll tell you quickly.

What happens next
  • Submit a short intake (role, revenue bracket, stack, pain area).
  • Pick a time immediately after submitting.
  • We deliver a workflow ROI map + 30-day build plan.