Primero AI closes seed round as LATAM's best-funded enterprise AI startup
Primero AI, a Mexico-based enterprise artificial intelligence platform, closed a $12 million seed funding round led by Kaszek and General Catalyst in August 2026, with participation from Definition, Conviction, and 8VC. The round also attracted angel investors linked to FEMSA, Bimbo, Aeroméxico, and Kimberly-Clark de México.
Co-CEO José Murillo described the company as LATAM's best-funded enterprise AI startup, a milestone arriving as venture capital returns to the region after prolonged contraction. Investment in Latin American startups surged around 2020 and 2021 but declined when the Federal Reserve raised rates and investors stopped betting on risk regions. Federal Reserve raised interest rates](), prompting investors to retreat from higher-risk emerging markets.
Primero was founded by Santiago Buenahora, Andrés Rosales, and Murillo, who previously co-founded Centrito, a low-cost e-commerce platform they closed in March 2025 after determining they lacked sufficient capital to reach required scale. Murillo returned remaining funds to investors and ensured 90 percent of the 45-person team secured new employment, many through his references.
Primero targets a different problem: large corporations that license AI tools but struggle to deploy them in core business processes. The company currently works with several dozen large corporations employing 20,000 to 40,000 people across Mexico, Colombia, and Brazil, including financial services firms where the platform automates SME credit approvals that previously required six to eight weeks but now complete in two hours.
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Primero has opened offices in Bogotá and Madrid and plans further regional expansion. For employers building tech teams in Colombia and hiring AI engineers and enterprise software talent across LATAM, the funding environment and Primero's growth trajectory signal where enterprise AI investment is concentrating.
Why Primero's platform approach signals growing demand for AI talent in LATAM enterprises
Primero positions itself as a product company rather than a consultancy, a distinction with direct implications for the technical talent required to serve enterprise clients. The company built what it calls an organizational AI brain platform that connects to clients' existing databases and preserves the context of their business processes, enabling customers to eventually deploy AI agents independently.
Murillo explained that consultancies typically build 100 disconnected solutions without shared maintenance or interoperability. Primero's platform provides a unified layer where AI deployments operate with continuous maintenance and integrated workflows. This architectural choice requires engineers who can build reusable, scalable systems rather than bespoke implementations.
The company's website describes a semantic layer that converts fragmented corporate data from ERP systems, Excel spreadsheets, Salesforce, internal APIs, Oracle, and Snowflake into unified operational context. According to MuleSoft's 2026 Connectivity Benchmark Report, organizations manage an average of 957 applications globally, but only 27 percent are connected. In Mexico specifically, 87 percent of companies report that technology fragmentation limits their ability to scale AI initiatives.
For companies hiring in Brazil, Colombia, and Mexico, Primero's approach illustrates a broader shift in enterprise software requirements. The platform must integrate legacy systems never designed for AI interoperability, a challenge particularly acute in Latin America where many large corporations operate older technology stacks. Engineers capable of building abstraction layers over heterogeneous enterprise environments, mapping informal business rules into machine-readable ontologies, and deploying auditable AI agents are increasingly central to enterprise digital transformation.
Primero's use cases span retail, financial services, consumer goods, government, insurance, and manufacturing, with applications including credit file processing, deduction reconciliation, claims evaluation, and production reporting. Each vertical requires domain expertise combined with platform engineering skills, suggesting sustained demand for cross-functional technical talent as enterprise AI adoption accelerates.
GENTY's hire developers in brazil guide offers additional context for employers planning their next hires. GENTY's hiring AI engineers and enterprise software talent across LATAM guide offers additional context for employers planning their next hires.
Enterprise AI adoption trends reshaping recruitment needs across Mexico, Colombia, and Brazil
The timing and structure of Primero's seed round reflect broader patterns in LATAM startup investment cycles. Murillo observed that the funding wave prioritized growth velocity over unit economics, while the subsequent correction swung to the opposite extreme. He criticized both approaches, arguing that founders should form independent opinions rather than follow the herd.
His advice to early-stage founders centers on building conviction in contrarian ideas. When Primero launched, the concept felt like a consultancy and was difficult to explain. Murillo noted that if a business does not yet exist, no one has attempted it, and entrepreneurs must trust their own understanding of the opportunity.
For employers and talent leaders, Primero's trajectory offers several workforce planning insights. First, backing from institutional investors reflects enterprise clients' need for vendor stability. Large corporations do not work with unfunded three-person garage operations because they require assurance that technology providers will remain operational over five, ten, or twenty-year horizons. This dynamic favors well-capitalized startups and creates competitive pressure for technical talent with enterprise software experience.
Second, the shift from customization-heavy consulting models to platform-based delivery changes the skill mix required. Platform companies need fewer implementation specialists and more product engineers, data architects, and DevOps professionals capable of building multi-tenant systems that serve diverse use cases without forking the codebase.
Third, Primero's regional footprint across Mexico, Colombia, and Brazil mirrors the geographic distribution of LATAM's largest corporations and suggests where enterprise AI talent demand will concentrate. Companies pursuing similar strategies will need distributed teams capable of navigating local regulatory environments, legacy technology landscapes, and industry-specific workflows.
The $12 million seed round (), among the largest for a LATAM startup at this stage in recent years, signals that investors are again willing to back ambitious enterprise software plays in the region. For organizations hiring AI engineers and enterprise software talent across LATAM, this capital influx will intensify competition for experienced platform engineers, machine learning specialists, and technical leaders with track records in complex enterprise deployments.
Primero's stated goal of enabling clients to deploy agents independently also points to a longer-term shift in enterprise AI maturity. As platforms lower the barrier to AI adoption, internal corporate AI teams will require different capabilities: less focus on building infrastructure from scratch, more emphasis on configuring, monitoring, and governing AI systems built on third-party platforms. This evolution will reshape job descriptions, compensation benchmarks, and talent development priorities across LATAM's largest employers.