AI agents for the systems you already have.

Governed agents for finance, procurement and operations on Oracle EBS and SAP — now extending to Salesforce, ServiceNow and the data platforms they sit beside — running inside your identity, approvals and audit trail, every action visible before it executes. No migration required.

Five-day discovery sprint, $5,000 flat — credited toward your project if you move forward.

AP Automationsample run
📄invoice_meridian_logistics.pdf
Run this yourself, with your own file or email →

From Tioga's own AI governance ledger · Jul 17–25 2026

$0.000753
Spend vs. cap
17
Calls logged
3
Backends in rotation
2 / 17
Paid vs. free-tier
Governed to:NIST AI RMFISO 42001EU AI Act

The integration problem

Enterprise AI projects stall because generic consultants build demos that can't connect to real systems. Your ERP, CRM and HRIS are locked behind custom APIs, legacy auth and security layers that require deep enterprise expertise to navigate.

The Tioga difference

I build MCP-native AI systems that speak your enterprise stack's language from day one. Your pilot runs on your real data, in your real environment — so the path to production is already built by the time I present results.

“I don't have client logos to show you yet — as a new practice, that's the truth. Try the product instead.”

Not ready to try the demos? Free ERP Agent-Readiness Checklist →
Live in our environment — demo data

Try It Right Now

Four real AI workflows. No signup. No mockups. The same Claude models built into every Tioga AI engagement.

See how I govern my own AI

The Governance Ledger is real operational data from Tioga's own AI routing gateway, mapped to NIST AI RMF — not a mockup. Every call logged, costed, and attributed as a byproduct of routing, not bolted on.

View the full ledger →
Governance Ledgerreal excerpt · not live
Real operational data, refreshed periodically — not a live-refreshing feed.

I integrate with your existing enterprise stack

SAP
Salesforce
ServiceNow
Oracle
Workday
SharePoint
Slack
Microsoft 365

Where to start

Three entry-point offers — each delivers a concrete, reviewable output in weeks, not quarters.

Pricing published up front, not gated behind a sales call. The $5,000 discovery sprint is credited toward whichever offer you move forward with.

Not sure where to start?

Five-day Discovery Sprint, $5,000 flat — credited in full toward whichever offer below you move forward with.

Book the sprint
Start here

AI Operations Assessment

Find the workflows AI can take off your plate

2–3 weeks. Map manual workflows across finance, HR, procurement, and operations. Rank automation opportunities by ROI and feasibility. Concrete plan in your hands.

AI Governance Readiness Assessment

Get audit-ready before regulators or customers ask

3–4 weeks. NIST AI RMF, ISO 42001, EU AI Act, and US state law gap analysis with a prioritized remediation roadmap. Sample executive summary included.

AI Agent Pilot

Build one working agent against your highest-value workflow

4–8 weeks. Production-ready agent. Governance built in from day one. Working pilot you can extend or hand off.

$25–50K

Plan a pilot

Plus ten more engagements across two practices — modernizing ERP with an agent layer, and governing enterprise AI end to end. See all services →

See what you actually get: sample discovery sprint scope, sample governance evidence excerpt, or sample readiness assessment summary.

What working with Tioga AI looks like

Not a generic AI consultancy. One founder who specializes in one thing: getting AI into production inside complex enterprise environments.

Tioga AI is built by Sukir Kumaresan, who spent decades on the operating side of enterprise systems — Oracle EBS, SAP, finance, HR, procurement — and the governance work that keeps those systems audit-ready. Every demo on this site, including the Governance Ledger above, is code Sukir wrote and infrastructure Sukir runs. No outsourced build, no slide deck.

Speed to value

My 5-day discovery sprint gives you a working prototype and a delivery plan before most firms finish scoping.

🔐

Enterprise-grade security

Security controls — role-based access, audit logging, and architecture aligned to SOC 2 Trust Services Criteria — so your systems of record stay under your control. No independent SOC 2 report exists yet.

🎯

Integration-first approach

I build for your stack from day one. No rip-and-replace. Your existing systems become more powerful.

🧪

No toy demos

Every pilot runs against your real data and real systems, built to carry into production, not thrown away after the demo.

📐

MCP-native builds

I specialize in Model Context Protocol — the emerging standard for connecting AI to enterprise systems at scale.

📈

Measurable ROI

I define success metrics up front. You see ROI calculations in the pilot, not after a 6-month engagement.

My Process

From first conversation to production deployment — with no ambiguity about what happens next.

01

Discovery Sprint

5 days · $5,000 flat

I map your systems, identify the highest-ROI AI opportunities and define a clear scope with your team. You get a working prototype and a detailed delivery plan — before any large commitment.

System audit · Use-case prioritization · Prototype · Delivery plan

02

Pilot Build

2–8 weeks · scope-dependent

I build a production-ready proof of concept integrated with your real systems. No toy demos — this runs against live data and real integrations. You see exactly what the full system will do.

Full integration · Real data · Stakeholder review · Go/no-go decision

03

Deploy & Scale

Ongoing

Full production deployment with monitoring, SLAs, ongoing support retainers and continuous improvement as your AI needs grow. I stay a partner, not a vendor.

Production deploy · Monitoring · Support SLA · Continuous improvement

New Standard

Model Context Protocol (MCP)

MCP is how frontier AI connects to enterprise systems. Tioga AI is built MCP-native from day one, with working connectors for SAP and Salesforce you can try on the MCP page. See the architecture, explore live demos and understand why your next AI project should be MCP-native.

Explore MCP →