Infino, an AI infrastructure startup co-founded by Ekechi Nwokah, has emerged from stealth with $7.5 million in seed funding led by Bessemer Venture Partners.
The company is building a unified data retrieval platform designed to help AI agents search and analyze information without relying on multiple database systems.
The round, announced October 6, 2026, included participation from Collide Capital, AIN Ventures, Integral Ventures, EchoVC Partners, and other investors. It marks the company’s first publicly announced financing round.
With Nwokah serving as CEO, Infino is targeting the infrastructure behind AI agents: the systems that allow them to find relevant information, retrieve precise results, and perform calculations across business data. Its approach brings several retrieval methods into one platform, reducing the need for companies to connect and maintain separate tools.
One System for Search and Analysis
Infino combines full-text search, vector search, and SQL in a single retrieval layer. These capabilities serve different purposes: full-text search finds information through words and phrases, vector search identifies related content based on meaning, and SQL supports structured queries and analysis.
Infino’s platform brings them together so an AI agent can search, filter, join, and aggregate data through one system.
For example, an AI agent investigating a company’s technology infrastructure might need to identify system errors, determine which applications were affected, and calculate how frequently those errors occurred.
Completing those tasks could require multiple queries across different databases. Infino embeds retrieval functions directly into SQL, allowing a single query to return ranked search results alongside exact counts, filters, joins, and calculations.
The company describes its technology as a unified retrieval layer that allows AI agents to work with one copy of the underlying data.
This approach is intended to reduce the infrastructure businesses must maintain as AI applications become more sophisticated and generate increasingly complex data requests.
Building on Existing Data Infrastructure
Infino’s platform operates over Apache Parquet, an open data file format commonly used for large-scale analytics. The company also stores its search indexes within Parquet files, allowing retrieval operations to use the same underlying storage architecture.
The platform supports data lake technologies including Apache Iceberg and Apache Hudi, while tools such as Spark and DuckDB can continue accessing the underlying data.
This compatibility allows Infino to integrate with existing enterprise data environments, potentially reducing the need for businesses to replace established infrastructure.
Cost reduction is another part of the company’s competitive positioning.
According to Infino, its architecture can deliver approximately 10 times lower infrastructure costs than conventional search and analytics systems.
Its website includes a pricing calculator comparing Infino with combinations of Elasticsearch, ClickHouse, Qdrant, and Fivetran.
In one modeled scenario involving one billion documents and 10 million monthly queries, Infino estimates monthly costs of $2,784, compared with $51,292 for the alternative technology stack.
That represents an estimated cost difference of approximately 18 times under the company’s assumptions.
These figures are based on Infino’s published pricing methodology and have not been independently validated. Actual savings would depend on workload characteristics, infrastructure requirements, and commercial agreements.
A Founding Team With Search and Technology Experience
Nwokah co-founded Infino alongside Asif Makhani, Murali Krishna, and Vinay Kakade. Krishna serves as chief architect, while Kakade leads engineering.
The founding team brings experience developing search, machine learning, and distributed data systems at technology companies including Amazon, Google, and LinkedIn.
Makhani previously founded and led Amazon CloudSearch at AWS. He also served as chief technology officer at Handshake and held leadership roles at Google and LinkedIn.
Nwokah brings entrepreneurial experience from the financial technology sector.
He previously co-founded Migo, a fintech company focused on expanding access to credit in emerging markets. Migo announced a $20 million Series B financing round in 2019 to support its expansion.
His experience building a financial technology business adds a commercial perspective to Infino’s technical founding team.
Nwokah has described AI agents as “the largest new consumer of data since the web browser.”
That observation reflects the changing demands placed on enterprise data infrastructure.
Traditional software generally retrieves information according to predefined instructions. AI agents can generate multiple requests dynamically, revise queries, and combine information from different sources as they work through complex tasks.
These capabilities create new requirements for the speed, flexibility, and cost of enterprise data retrieval.
An Open-Source Engine and Commercial Cloud Platform
Infino is pursuing a business model that combines open-source software with managed cloud services.
Its core retrieval engine is available on GitHub under the Apache 2.0 open-source license, allowing developers to deploy and modify the technology within their own infrastructure.
The company also offers Infino Cloud, a hosted service that provides managed access to its retrieval technology, along with enterprise deployment options.
This model allows developers to experiment with the platform while providing commercial services for organizations seeking managed infrastructure and additional capabilities.
Infino reports that its technology is already supporting workloads involving billions of records across government, document processing, computer-aided design, and real-time analytics.
Its website identifies the United States Government and Bazinga Labs among organizations associated with its platform, although detailed customer relationships, contract values, and revenue figures have not been publicly disclosed.
These applications illustrate the range of data-intensive environments Infino is targeting as businesses explore how AI agents can support operational workflows.
Venture Capital Investment in AI Infrastructure
Infino’s financing comes as venture capital firms continue investing in the technology required to support AI applications at scale.
Bessemer Venture Partners, which led the round, has an established investment history in enterprise software, cloud computing, and developer infrastructure.
The participation of Collide Capital, AIN Ventures, Integral Ventures, and EchoVC Partners brings additional investors with experience backing emerging technology companies into the financing.
With $7.5 million in seed funding, Infino is positioned to continue developing its retrieval technology and expanding its commercial reach.
As more businesses deploy AI agents, the company’s next stage will involve demonstrating how its architecture performs across production environments, translating its claimed cost advantages into measurable customer savings, and expanding adoption of its open-source and cloud offerings.
