BUILT BY
OPERATORS
FOR OPERATORS
We're former CFOs, CIOs, and COOs who lived through failed AI pilots and vendor promises. NavaraAI exists because we needed it ourselves—and couldn't find it anywhere.
The problem we're solving
Enterprise AI has a massive credibility problem. Vendors overpromise. Consultants oversell. Projects stall in endless pilots. Meanwhile, finance teams still close books manually, procurement still chases invoices, and HR still drowns in onboarding paperwork.
The technology works. The implementation model doesn't. Traditional software companies sell licenses and walk away. Consulting firms build custom solutions that break the moment they leave. AI startups demo impressive prototypes that can't handle enterprise complexity.
NavaraAI takes a different approach. We deploy engineers who understand your systems. We build workflows tailored to your processes. We measure success by your outcomes, not our revenue. And we don't leave until it works.
How we work
Forward-Deployed Engineers
We don't sell software and hope you figure it out. Our engineers work alongside your team, understand your processes, build solutions for your reality, and stay until they deliver results. No handoffs to inexperienced implementation partners.
Platform Expertise Required
Every team member has deep expertise in SAP, Oracle, Workday, or other enterprise platforms before joining NavaraAI. We don't learn your systems on your time. We've already implemented them dozens of times and know exactly how they work.
Outcomes Over Outputs
We can tie pricing to business results. Reduce close time by 20%? Save 1000 hours per quarter? Cut payment errors by 85%? You define success metrics upfront, and we're accountable for hitting them. Shared risk, shared reward.
Security By Design
Your data never leaves your environment. Our AI operates inside your security perimeter, using your access controls, respecting your compliance requirements. No data sharing with third parties. No training on your information. Period.
The founding story
NavaraAI started in 2019 when three enterprise leaders found themselves at the same conference, complaining about the same problem over drinks. They'd all tried implementing AI in their organizations. They'd all spent millions on pilots that never scaled. They'd all watched as vendors disappeared after signing contracts.
Sarah Chen had just finished a brutal month-end close as VP Finance at a Fortune 500 company. Fifteen days of manual reconciliations, Excel gymnastics, and weekend work—despite using a "best-in-class" ERP system that supposedly had AI built in.
Marcus Rodriguez was running IT operations at another enterprise, managing five different vendors who all claimed their AI would revolutionize his help desk. None of them understood how his systems actually worked. All of them blamed his "legacy infrastructure" when their demos failed.
Jennifer Park had spent years at McKinsey advising clients on digital transformation. She'd seen the pattern: executives excited by AI demos, procurement teams negotiating massive deals, IT teams struggling with implementation, and business users reverting to their old workflows within months.
The problem wasn't the technology. GPT-3 had just been released. Computer vision was mature. NLP worked. The problem was that nobody was building AI for the reality of enterprise operations—messy data, complex integrations, compliance requirements, change management, and the fact that real businesses can't afford to replace systems that run critical operations.
They decided to build the company they wished existed. One that understood enterprise platforms deeply. One that deployed engineers to customer sites. One that tied compensation to customer outcomes. One that treated security and compliance as requirements, not afterthoughts.
Today, NavaraAI serves over 240 enterprises globally. The founding team still reviews every major deployment. Because they remember what it was like to be the customer—and they're determined never to become the vendor they used to hate.
Leadership team
Former operators from Fortune 500 companies who've lived the problems we're solving. No theoretical experience—just decades in the trenches.
Sarah Chen
Former VP Finance at Salesforce, leading 200+ person team through hypergrowth. Built financial systems that scaled from $1B to $10B revenue. Stanford MBA, CPA. Knows every pain point in enterprise finance operations because she lived them all.
Marcus Rodriguez
15 years building enterprise platforms at Oracle and SAP. Led implementations for 50+ Global 2000 companies. PhD MIT in distributed systems. 8 patents in enterprise AI. Actually understands how ERP systems work under the hood.
Jennifer Park
Built AI products at Google and Palantir. Former McKinsey consultant focused on enterprise digital transformation. Spent years watching AI projects fail and learned exactly what not to do. Product philosophy: solve the problem, not the demo.
David Okonkwo
20+ years enterprise software sales at Workday. Built multiple $100M+ ARR businesses from zero. Refuses to sell deals that won't succeed. Believes commission should be tied to customer renewals, not initial contracts. Actually reads implementation reports.
What we believe
Customer success is the only metric that matters
We don't celebrate closed deals. We celebrate customer outcomes. A sale isn't success—it's the beginning of our real work. We measure ourselves by retention rates, not new logos. Our compensation structure reflects this: renewals matter more than new business.
Intellectual honesty over politeness
If your project will fail, we'll tell you before we take your money. If your timeline is unrealistic, we'll say so. If your data quality will prevent success, we'll be explicit about the work required. We'd rather have difficult conversations upfront than disappointing results later.
Expertise is earned, not claimed
Every engineer has 5+ years implementing enterprise platforms before touching customer work. Every solution architect has scars from failed deployments. Every customer success manager has actually worked in the functions they support. We don't hire people who "learn quickly"—we hire people who already know.
Outcomes, not activity
We don't track hours, meetings, or status reports. We track whether the month-end close is faster. Whether invoice processing errors dropped. Whether employees got onboarded without manual work. Results are binary: it works or it doesn't. Everything else is noise.
Security and compliance are not negotiable
We've never asked a customer to compromise security for convenience. Data stays in customer environments. Access follows least-privilege principles. Compliance is designed in, not retrofitted. If a customer requirement conflicts with our standard approach, we adapt our approach—never their security posture.
No shelfware, ever
Every license sold must be actively used within 90 days or we refund it. We have a team whose only job is ensuring adoption. If a customer isn't getting value, we'd rather lose the revenue than keep selling them something that sits unused. Our renewal rates prove this approach works.
By the numbers
Where we work
Three office hubs plus distributed teams globally. Work from where you're most effective.
Join the team
We're hiring operators and engineers who want to build AI that actually works in enterprise environments.
Talk to our team
Want to know if we're right for your organization? Let's have an honest conversation about your challenges.