Dataline Labs secures £750k pre-seed to enable natural-language queries of enterprise data
This article covers Dataline Labs, a London-based AI startup, which has raised £750k in a pre-seed funding round led by Haatch Ventures with participation from the British Business Bank. The funding will support team expansion, the roll out of its MIRA AI platform to enterprise clients and delivery of Ministry of Defence Digital Supply Chain Hub Defence Testbed Accelerator projects, with the platform intended to let non-technical teams query fragmented enterprise data in plain English.
Dataline Labs, a London-based AI startup, has raised £750,000 in a pre-seed funding round led by Haatch Ventures with participation from the British Business Bank. The funding will be used to expand the team, roll out its MIRA AI platform to enterprise clients and support the company’s work with the Ministry of Defence’s Digital Supply Chain Hub Defence Testbed Accelerator. This matters because the product aims to let non-technical teams query fragmented enterprise data in plain English, potentially speeding decision making across departments.
Why it matters
Many organisations still struggle with data trapped in disconnected systems, spreadsheets and legacy software, which creates bottlenecks for product, operations and finance teams that depend on timely insights. Tools that reduce reliance on engineering or specialist data teams can cut cycle times for analysis and surface operational problems faster.
Dataline Labs’ selection for the MoD Defence Testbed Accelerator is notable because it puts the startup into projects with defence manufacturers such as Babcock, Thales and Rheinmetall BAE Systems Land — firms that manage complex supply chains and have strict requirements for data integration and security.
Inside the product
Dataline Labs sells a platform called MIRA AI that ingests multiple data sources, normalises fragmented datasets and lets users query them using natural language. The company positions the product as a way to extract answers without months of engineering work or specialist expertise.
Customers to date include projects across smart buildings (monitoring and optimisation of building systems), asset management (tracking and condition reporting), manufacturing (operational metrics), business media (audience and content analytics) and ESG reporting (aggregating environmental and governance data). These examples demonstrate the platform’s enterprise focus rather than a single vertical product.
Who are the investors?
The round was led by Haatch Ventures with participation from the British Business Bank. The new capital is earmarked for hiring, product rollout to enterprise clients and delivery of MoD-related projects.
In the announcement, Sophie Weavers-Wright, Head of Platform at Haatch, said:
Evan and Chris have built something genuinely impressive in a short space of time. Two first-time founders going from zero to MoD selection in a short period of time tells you everything about the quality of the technology and the team. We're excited to back them as they scale.
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Founder perspective
The business was founded by Evan Shapiro (CEO) and Chris Lawson (CTO). Both are first-time founders who built the core product and secured early enterprise engagements that led to MoD selection.
In the announcement, Evan Shapiro, Co-founder & CEO at Dataline Labs, said:
We spent years watching companies drown in their own data. The information was there, but getting to it meant waiting on overloaded engineering or data teams, with dozens of tasks ahead of yours. We started Dataline Labs because we believed there had to be a faster way - and now we're proving it with a vote of confidence from investors and the MoD.
The bigger picture
The raise highlights ongoing investor interest in enterprise AI tools that address practical data fragmentation rather than consumer-facing AI. Public backing via the British Business Bank and MoD engagement also shows how government programmes and public funds can accelerate the validation of early-stage technology for regulated sectors such as defence.
For the UK and European ecosystem, Dataline Labs’ path — pre-seed funding combined with accelerator-backed pilot projects — is a familiar route for startups seeking to turn early engineering work into recurring enterprise contracts. If MIRA AI can scale across multiple regulated industries while meeting procurement and security requirements, it could become a useful example of how AI and data tooling firms move from proof of concept to commercial deployments.
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