AI business automation
AI Business Automation: We Build It, Deploy It, Run It.
We are an AI automation agency for mid-market companies. We design, build, and operate production AI workflows across sales, marketing, and back-office — fixed pricing, weekly KPI reporting, governed from day one. No slides. No pilots in perpetuity.
In one sentence
AI business automation from our agency is a phased engagement (Discovery 2-3 weeks → Build 6-10 weeks → Run continuous) that ships a production AI workflow on your real data, moves a named KPI by 30-90% against your baseline, and is governed by versioned prompts, audit logs, and reviewer queues from day one.
Key facts
- Engagement model
- Phased fixed-price
- Discovery
- $5-8k · 2-3 weeks
- Build
- $15-40k · 6-10 weeks
- Run
- $2-6k/mo · month-to-month, optional
- Time to production
- 6-10 weeks thin-slice
- Year-1 total
- $25-90k typical
- Verticals served
- Sales, Marketing, Back-Office
- Industries
- 42 covered (banking, healthcare, legal…)
- Governance
- Versioned prompts · audit logs · NIST AI RMF
What we automate
Three verticals where AI business automation has the cleanest signal-to-noise on impact. Pick the one with the most pain and volume; we scope the first workflow in Discovery.
AI Sales Automation
Sales
Outbound prospecting, lead qualification, CRM enrichment, meeting scheduling, and pipeline reporting.
- →Sales Prospecting (signal-driven outbound at 14-22 SQLs/week per SDR)
- →Lead Qualification (CRM auto-scoring with reviewer escalation on edge cases)
- →Revenue Operations (pipeline forecasting + AI-drafted ops reports)
Outbound throughput typically +3-5×, cost per qualified meeting -75%
AI Marketing Automation
Marketing
Content production, lifecycle orchestration, paid-media operations, and landing-page production at scale.
- →Content Marketing (briefs → drafts → SME review → publish)
- →Lifecycle Marketing (segment-aware email + in-product flows)
- →SEO Landing Pages (programmatic with quality gates)
- →Paid Media Operations (creative iteration + bid management)
Content velocity 3-8× with reviewer-approved quality bar
AI Back-Office Automation
Back-Office
Operations, finance, HR, compliance, and customer service workflows where AI handles volume and humans handle judgment.
- →Customer Service Automation (intent classification + grounded responses)
- →Document Processing (extraction + validation + downstream system updates)
- →Compliance Operations (alert triage + reviewer queues + attestations)
- →Finance Back Office (reconciliation, invoice processing, exception routing)
Cycle time -70 to -90%, error rate -60 to -80%, audit-ready logs
How we deliver
Three phases, billed separately. You commit one phase at a time. Discovery is the only commitment to start.
Phase 1 · Discovery
2-3 weeks · $5-8k
We map the current workflow, capture the KPI baseline, document system access requirements, identify the risk lens, and write a scoped Statement of Work for Build with a fixed price. Output: a 25-page Discovery report + 8-page Build SoW.
Phase 2 · Build
6-10 weeks · $15-40k
We build six tangible artefacts: workflow map (current and target), labelled test set (200-1000 cases), prompt and retrieval repository (versioned), integration layer (against your systems), reviewer queue (with SLAs), operating dashboard (KPIs, drift detection). Thin-slice ships to production traffic by week 6.
Phase 3 · Run (optional)
$2-6k/month · month-to-month
Weekly KPI report against Discovery baseline. Prompt refresh against new edge cases. Retrieval index updates. Reviewer-queue calibration. Quarterly attestation pack for risk officers. By month 6, your team takes over Run if desired — every artefact is handed over.
What production looks like
Most AI engagements stop at the prototype that works on cherry-picked inputs. Ours ship to production traffic with KPIs, SLAs, and governance you can defend in front of a CFO, a risk officer, or an auditor.
What 'production' means here
Real data, real reviewers, real KPIs. Not a sandbox demo on cherry-picked inputs. The thin slice ships to production traffic by week 6 of Build and runs continuously after that.
SLAs we commit to
Reviewer-queue throughput <24h average. Workflow uptime >99.5%. Quarterly attestation packs delivered in <5 days from quarter-end. Documented in the Build SoW.
Governance shipped on day one
Versioned prompts, audit logs on every inference call, source allow-lists, NIST AI RMF mapping for regulated workflows. Reviewable by your risk officer before production launch.
KPI accountability
Baseline captured in Discovery. Actuals reported weekly during Run. No 'pilot in perpetuity' — by day 90 leadership has the data to expand or stop.
Industries we've automated for
42 industries covered, each with its own engagement template, benchmarks, and risk lens. A sample of the high-volume ones:
Frequently asked questions
What is AI business automation?+
AI business automation is the use of AI as the operating layer of a business workflow — intake, classification, retrieval, drafting, decisioning — with humans handling judgment, exceptions, and policy. It is distinct from RPA (rule-based) and from 'AI features' (a chat button bolted onto an existing process). The workflow itself is redesigned around AI.
How much does AI business automation cost?+
Phased fixed-price. Discovery: $5-8k for 2-3 weeks. Build: $15-40k for 6-10 weeks depending on integration depth and risk lens. Run: $2-6k/month, optional, month-to-month. Total year-1 typically $25-90k for a focused workflow — orders of magnitude below traditional consulting builds for an equivalent production system.
How long does an AI business automation project take to deploy?+
Thin-slice production deployment in 6-10 weeks from Discovery start: 2.5 weeks Discovery (scope, baseline, systems, risk model), then 6-10 weeks Build (architecture, eval harness, reviewer queue, KPI dashboard, thin-slice shipped to production traffic). Optional Run phase runs continuously after that with weekly KPI reporting.
What business processes can be automated with AI in 2026?+
Any high-volume, structured-but-messy workflow with a measurable outcome. The best candidates: customer service (intent + grounded answers), document processing (extraction + validation), sales prospecting (signal-driven outbound), compliance triage (alert routing + evidence assembly), executive reporting (data → narrative), claims/case processing (intake → decision support). The wrong candidates: politically charged decisions with no measurable baseline, or workflows with insufficient volume to justify the build.
How is AI business automation different from RPA or workflow automation tools?+
RPA executes rule-based scripts on structured data — it breaks when the input shape changes. Workflow tools (Zapier, n8n) chain pre-defined integrations — they don't reason. AI business automation handles unstructured input, adapts to exceptions, and makes context-aware decisions while routing low-confidence cases to humans. It is the operating layer above the integration layer, not a substitute for it.
Do we own the AI workflow at the end of the engagement, or are we locked in?+
You own everything: prompts, evaluation harness, code, configs, runbook, operating playbook. Run is month-to-month with no notice period. Most clients keep us on Run for 6-12 months while their team learns the operating model, then take it in-house. The Build SoW includes a full handover plan; the engagement is designed to survive our absence.
Start here
Start with a 2.5-week Discovery
$5-8k, fixed price, 2-3 weeks. Output: a scoped Statement of Work for Build with a fixed price and a documented baseline. The only commitment to start.