Our verdict
Making Sense has built software for mid-market companies for about 20 years, and in October 2026 Anthropic made it a Select partner in the Claude Partner Network on the strength of two production deployments. It suits a mid-market or private equity-backed company that wants a nearshore team to add an AI assistant or agent to a product it runs today, and it is less suited to a large enterprise looking for a strategy-led transformation program.
The right buyer
- Mid-market software companies adding AI to a live product. For the email platform Doppler it built ECO IA, a Claude assistant that runs in more than 4,800 accounts (Techli).
- Buyers who want the skills to stay in-house. It often embeds its engineers in the client’s team so the capability remains after the contract ends (Techli).
- Companies in healthcare, fintech, and logistics, where much of its agentic AI work sits (Techli).
Reasons to look elsewhere
- Its public Claude record rests on two clients, Doppler and Viallion.
- Its delivery teams are in Argentina, Mexico, and Colombia, so a buyer who needs an onshore US team should look elsewhere.
Making Sense, At A High Level
Making Sense started in Mar del Plata, Argentina, in 2006 and calls itself a product builder for the mid-market, with design, engineering, project management, and quality control in one team (about page; Red Argentina IT). Cesar D’Onofrio is its CEO and a founder, and Sergio Marchetti is COO and a founder (about page).
- Headquartered at 228 Hamilton Avenue in Palo Alto, California, with offices in the US, Argentina, Mexico, and Colombia (about page).
- More than 400 people, according to its Red Argentina IT member profile; we estimate annual revenue at $18 million to $22 million (Red Argentina IT).
- A Select partner in Anthropic’s Claude Partner Network Services Track since October 2026, with 20 Anthropic-certified staff; the team also holds OpenAI credentials (Techli).
- For Viallion, a trading automation platform, it rebuilt the engineering workflow around Claude Code, and releases that took two to three months now ship in about a week, according to the firm (PA Chronicle).
Scores by criterion
We scored Making Sense from its about page, its member profile, and October 2026 coverage of its Claude partnership. The delivery model scores highest; commercial clarity scores lowest because it publishes no terms.
| Criterion | Weight | Score | Basis |
|---|---|---|---|
| Production track record | 20% | 7.0 | Two publicly identified production AI deployments plus more than 100 projects over about 20 years. |
| Technical depth | 15% | 7.0 | Claude assistants with prompt caching and cost monitoring; agentic workflows. |
| Industry depth | 10% | 6.5 | Healthcare, fintech, logistics, agtech, and public safety. |
| Delivery model and handoff | 15% | 7.5 | Engineers embedded in the client team, with the capability handed over. |
| Commercial clarity | 10% | 5.5 | No published rates or minimums. |
| Platform independence | 10% | 7.0 | Claude and OpenAI credentials; builds on the client’s stack. |
| Stability and scale | 10% | 7.0 | About 20 years old with more than 400 people. |
| Independent evidence | 10% | 6.5 | Anthropic Select status and trade press coverage; few public client reviews. |
| Overall | 100% | 6.8 | Weighted average |
Where Making Sense fits
Making Sense is used by mid-market and private equity-backed US companies that want a nearshore product team able to design, build, and run an AI feature inside software they sell. On price it is a mid-market nearshore option, below US onshore consultancies and above offshore staffing shops. Competitors on this site include Arionkoder and Leanware for Latin American product teams, Rootstrap for AI product builds, and Gorilla Logic for nearshore engineering at a larger scale.
| Need | Fit | Why |
|---|---|---|
| An AI assistant inside a SaaS product | Strong | It built and runs ECO IA for Doppler in more than 4,800 accounts. |
| Moving an engineering team onto Claude Code | Good | Its Viallion work cut release cycles from months to about a week. |
| A board-level AI strategy for a Fortune 500 | Weak | Its focus is product delivery for the mid-market. |
| Agentic workflows in a regulated industry | Good | Much of its agentic work is in healthcare, fintech, and logistics. |
What clients and leaders say
Making Sense’s leaders and clients describe its work in published announcements. One buyer concern is written from public facts about the firm.
“Knowing what a change will touch inside a company still takes people who understand that business: the system billing depends on, the data a regulator will ask about, the team that has to operate it the next morning.”
“That gives clients a public, verifiable reference for what we’ve delivered, which makes choosing who to work with less of a leap of faith.”
“Their AI work was strong, but the public examples were only two clients, so we asked to speak to both before we signed.”
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: PA Chronicle coverage, which says its case rests on Doppler and Viallion.
Who leads Making Sense
Cesar D’Onofrio is CEO and a founder of Making Sense (about page).
