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Hang Ten Systems
Palo Alto firm, founded by former Infosys chief executive Vishal Sikka, that advises very large companies on AI and builds production software with an internal framework called Hobie.
Enterprises above about $10 billion in revenue that want a small team to build production software, with the customer's own reviewers still certifying the result.
Buyers who want a packaged product with a login, or a staff-augmentation bench of dozens of consultants.
Verdict
Hang Ten Systems is a Palo Alto company founded in May 2026 by former Infosys chief executive Vishal Sikka. It advises companies that typically take in more than $10 billion a year, and it builds and modernizes their software. Engineers use an in-house framework called Hobie, which packages reusable skills for regulated industries. Customers include Fresenius Kabi, Saudi Aramco, and Siemens Energy, across the United States, Europe, the Middle East, and Asia. Large companies hire Hang Ten for software built around their own process, including projects they had previously put off, and a customer or an outside party still certifies the result.
On September 16, 2026, TechCrunch reported that Hang Ten added $53 million to its seed funding, led by Xora, Temasek's early-stage platform, five weeks after a $32 million seed led by Mayfield. Total funding is $85 million. Mayfield participated again, along with Aramco Ventures, Intel CEO Lip-Bu Tan, Micron CEO Sanjay Mehrotra, and Yahoo co-founder Jerry Yang, who sits on the board. Sikka said the firm is working a mix of customers and late-stage prospects across 21 major enterprises, has multiple seven-figure contracts, and is pursuing eight-figure deals. One multimillion-dollar contract was signed within 25 days of a first meeting. Headcount is about 20 to 25 people in the United States, the Middle East, and Australia. Co-founder and chief design officer Sanjay Rajagopalan said some projects use about two to four people where about 30 might have been used before, and that the firm promises customers a 10-fold improvement in cost, speed, or a combination of the two (TechCrunch).
Score Breakdown
How Hang Ten Systems scores in the categories that matter to its buyers.
Pricing
Hang Ten sells project work to large enterprises. TechCrunch reported multiple seven-figure contracts and pursuit of eight-figure deals (TechCrunch).
The Field at a Glance
Where Hang Ten Systems ranks among AI strategy & implementation vendors we reviewed, by Overall Score and relative typical engagement cost.
Hang Ten Systems scores 6.8, fourth of the six AI strategy & implementation firms we reviewed, behind 7T (8.7), Provectus (7.9), and Logic20/20 (6.9) and ahead of Distyl AI (6.7) and Tribe AI (6.6). Typical engagement cost sits in the $$$ band with the enterprise build firms.
Use-case matrix
| Use case | Fit | Notes |
|---|---|---|
| Mission-critical software for a large enterprise | Strong | Named customers include Fresenius Kabi, Saudi Aramco, and Siemens Energy. |
| AI advice plus the build | Strong | The firm both advises and writes the software. |
| Regulated industries | Strong | Hobie packages skills for that work. |
| A product you log into next week | Weak | The offer is a services engagement. |
| A 30-person integration bench | Weak | The firm describes crews of about two to four, with outside certification. |
Review Excerpts
Representative buyer views drawn from public information about Hang Ten Systems. Paid reviews and pay-for-play sites were excluded.
“The engagement is the software itself, built with the firm's Hobie framework for a company our size.”
Representative buyer view
“A few engineers build a system the company had postponed, and its own reviewers certify the result.”
Representative buyer view
“A claimed tenfold gain on cost or speed still needs an outside party to certify the result.”
Representative buyer view
Where customer reviews couldn't be found, our analysts attempted to give a voice to buyer sentiment, drawing on real information from review sites, forums, and product documentation.
Based on: TechCrunch’s seed report
Methodology
This page is an independent evaluation of Hang Ten Systems for buyers comparing options in AI strategy & implementation. AI Industry Reviews accepts no sponsorships, advertising, or pay-for-placement fees. Hang Ten Systems did not pay for this review.
What we scored
The headline number is an Overall Score on a 0-10 scale. Eight criteria fall under it in two groups.
- Buyer outcomes (for AI strategy & implementation)
- Enterprise software delivery
- Regulated-industry project fit
- Team depth at four months old
- Work across model vendors
- Company & commercial
- Innovation & product leadership
- Project management & communication
- Pricing
- Contract fairness
Pricing measures whether the price looks fair for the value delivered, including packaging and renewal friction that show up in real buying cycles.
Score Composition
| Input | Weight | What it covers |
|---|---|---|
| Reviews | 40% | A proprietary read of what practitioners say about likes, complaints, and day-to-day use, including public review sites, forums, and private chat rooms. Paid reviews and pay-for-play sites are out of scope. |
| Product | 35% | Hands-on look at screens and workflows. |
| Pricing | 15% | Whether the price looks fair for what you get. |
| Docs & training | 10% | Docs, tutorials, and training material. |
How we balanced the evidence
The Overall Score is the simple average of the eight criteria. Recommendation language follows that score and the use-case matrix above.
Scope
Hang Ten Systems is graded here as AI strategy & implementation. Criteria scores can move as more review volume and product checks are added.