Finance & ops automation
Invoice processing, expense reconciliation, payment routing, expense classification. Built for workflows where vanilla AP software doesn't fit.
Service
AI Workflow Automation
Take manual operations off your team's plate.
We build production AI that automates the operational work your team does manually today: finance reconciliation, support triage, document processing, internal Q&A. Custom-built for your stack, not generic SaaS.
custom n8n workflow builds →for custom WhatsApp AI, see WhatsApp Business →for cross channel marketing automation, see Marketing Automation →
Where we focus.
Six application areas where this service ships measurable results, chosen against the failure modes most growing businesses hit.
Customer operations
Support triage with confidence-based escalation, ticket routing, customer-facing Q&A grounded in your actual product data.
Document & data processing
Contracts, claims, applications, forms, extracted, classified, routed automatically with full audit trails for regulated workflows.
HR & people operations
Resume screening with explainable scoring, candidate routing, onboarding workflows, internal-policy Q&A, built to your hiring rubric, not a generic ATS.
Internal knowledge & Q&A agents
Retrieval grounded on Slack, Notion, Confluence, SharePoint, and Google Drive. Cited answers, source links, role-based access so people only see what they should.
Compliance & risk workflows
KYC and AML triage, sanctions screening, transaction monitoring, audit-trail generation. Human-in-the-loop on every high-stakes decision.
Reality check
The pilot worked. The rollout is where it died.
Almost every failed automation project has the same shape: a pilot that impressed everyone, then nothing. MIT's research puts a number on it, 95% of generative AI pilots produce no measurable financial impact, and identifies the reason precisely. The gap is not engineering talent. It is the complexity of connecting AI to the actual systems of record, the ERP, the ticketing platform, the knowledge base, that the pilot deliberately avoided.
That avoidance is why the pilot looked easy. It ran on exported data, a clean sample, and nobody's live queue. Production is the opposite: partial records, systems that time out, permissions that vary by user, and an ops team who will route around anything that is wrong twice.
So the work that actually decides success is unglamorous. Reading and writing to systems that were never designed for it. Deciding what happens on low confidence. Making the audit trail good enough that a manager will trust the output without re-checking it. That is the part we build, and it is the part pilots skip.
Related work
Where we've shipped this in production.
B2B RENTAL · 25-YR LEADER Equipp (Ralco Group)
Rental operations automation for the digital arm of a 25-year hardware leader. B2B and B2C in one platform.
Read case study -> REAL ESTATE · WHATSAPP AIKlickie
WhatsApp-first AI that automates broker workflows: listing intake, buyer Q&A, lead qualification.
Read case study ->
B2B SAAS · OUR OWN PRODUCT CampaignHQ
Our own production SaaS: automated email + WhatsApp campaigns, AI chatbots, smart inbox. AWS Partner.
Read case study ->
FINTECH · YC S20 Volopay
How KUMO's co-founders built Volopay's first production version as its founding engineers, and how Volopay became a long-term KUMO client the same team scales as its external software and AI partner.
Read case study ->
B2B PROCUREMENT Racepoint
Building Racepoint, a multi-agent LLM B2B procurement platform where AI agents handle queries, configuration, and quotes.
Read case study ->What it costs
What this costs
The short answer
A first automated workflow runs $20K to $50K over 4 to 16 weeks, shipped into production with human checkpoints where being wrong is expensive. Multi-workflow builds run $50K to $100K. If an off-the-shelf tool or an n8n workflow genuinely covers your case, we will tell you, and we build those too.
Starter Build
$20K to $50K
4 to 16 weeks
A first production build, shipped end to end with evaluation and human review built in.
Grow Build
$50K to $100K
16 to 24 weeks
Multi-workflow or multi-feature platform work, re-engineered for scale.
Support and Growth Team
$5K to $10K per month
Ongoing, cancel with 30 days notice
The engineering team on retainer once it is live: new work, evals, and monitoring.
These are our three live engagement bands, the same across every KUMO service. Not sure which one fits? That is exactly what the first call is for.
Technologies and platforms
Assembled for your build.
FAQ
How is this different from buying off-the-shelf workflow tools? +
We build custom when your workflow spans systems no single tool connects, when your data is domain-specific, or when compliance needs more than a generic vendor gives you. You get automation shaped to how your business actually runs, and you own it.
Will the AI work reliably in production? +
Production agents have guardrails by design: input validation, confidence thresholds with human escalation, activity logging. Production AI never has unbounded autonomy on irreversible actions.
Can you integrate with our existing tools (Slack, HubSpot, etc.)? +
Yes. Common integrations: Salesforce, HubSpot, Slack, Zendesk, Jira, NetSuite, QuickBooks, Xero. If your tool has an API, we can integrate.
What does a typical engagement look like? +
Discovery and scope take 2-3 weeks. A single workflow ships in 8-12 weeks; multi-workflow builds run 12-16. We work in two-week milestones with a working artifact at the end of each, so you can pause, redirect, or expand based on what's actually working.
Do we own the AI after delivery? +
Yes. All code, prompts, configurations belong to you on milestone payment. No vendor lock-in, no ongoing licensing.
How much does AI workflow automation cost? +
A first workflow runs $20K to $50K over 4 to 16 weeks. Multi-workflow builds run $50K to $100K. Ongoing engineering is $5K to $10K per month.
Why do so many AI automation pilots fail? +
Research puts pilot failure between 88% and 95%, and the cause is consistently integration rather than the model. Pilots run on exported sample data and avoid the systems of record; production cannot. The fix is building against real systems from the start.
What happens when the AI is not sure? +
It escalates. Every workflow gets a confidence threshold and a defined human path, and every decision is logged. Automation never gets unbounded authority over an irreversible action.
Can you automate a process that spans several systems? +
That is usually the reason to build custom rather than buy. Single-system automation is well served by off-the-shelf tools; workflows crossing an ERP, a CRM and a document store are where vendor tools stop.
Tell us what you're solving for.
We'll listen first, ask the right questions, and follow up with a clear proposal.