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Here's our vision: connectivity, clean data, and reliability will decide which labs win in the future. Not closed-loop theater.",[],{"dimensions":351,"alt":354,"copyright":355,"url":356,"id":357,"edit":358},{"width":352,"height":353},2880,2160,"Lab of the Future Manifesto",null,"https://images.prismic.io/unitelabs/JUZRgEGDqRY2A56q_lotf-manifesto-hero-1440x1080_2x.png?auto=format,compress","JUZRgEGDqRY2A56q",{"x":26,"y":26,"zoom":38,"background":359},"transparent","UniteLabs","2026-07-28",[363,525,543,627,645,783,802,851,862],{"variation":364,"version":365,"items":366,"primary":367,"id":523,"slice_type":524,"slice_label":355},"default","initial",[],{"content":368},[369,372,375,388,391,396,399,410,413,423,426,432,441,452,457,462,467,470,475,478,481,487,494,500,503,506,509,514,520],{"type":347,"text":370,"spans":371,"direction":344},"The skeptics were right. For the last 20 years, the self-driving “Lab of the Future” was largely a chimera.",[],{"type":347,"text":373,"spans":374,"direction":344},"Very few companies actually reached those sunlit uplands, due to the massive resources required. And even fewer companies proved it was worth the trip (or shared the journey).",[],{"type":347,"text":376,"spans":377,"direction":344},"We believe it’s time to focus on building the foundations instead: instrument connectivity, clean data, and reliability. These three factors will decide which labs win in the next decade.",[378,382,385],{"start":379,"end":380,"type":381},67,90,"strong",{"start":383,"end":384,"type":381},92,102,{"start":386,"end":387,"type":381},108,119,{"type":347,"text":389,"spans":390,"direction":344},"For this manifesto, we outline our company vision, based on deep in-the-trenches experience, and our frequent conversations with many (most?) of the smartest minds in lab automation.",[],{"type":347,"text":392,"spans":393,"direction":344},"Warning: not everyone agrees with us. And that’s ok. We’re betting the farm on it anyway.",[394],{"start":26,"end":395,"type":381},7,{"type":347,"text":397,"spans":398,"direction":344},"And now the market's starting to say it too. In June 2026, senior automation and R&D leaders at major pharma and biotech companies like Roche, Novo Nordisk, Takeda, BioNTech SE, and Lonza signed an open letter demanding open standards in lab automation: no more inscrutable black boxes, and freedom from single-vendor lock-in.",[],{"type":347,"text":400,"spans":401,"direction":344},"Many more automation leaders will likely follow soon (read the open letter here).",[402,409],{"start":403,"end":404,"type":405,"data":406},75,79,"hyperlink",{"link_type":163,"url":407,"target":408},"https://sila-standard.com/letter-of-intent-on-open-standards-for-life-sciences/","_self",{"start":403,"end":404,"type":381},{"type":347,"text":411,"spans":412,"direction":344},"In their words: \"AI is not the starting point of the Lab of the Future, it is one of the outcomes enabled by interoperability.\" We've been building on exactly that premise since our inception.",[],{"type":414,"url":415,"alt":416,"copyright":355,"dimensions":417,"id":420,"edit":421},"image","https://images.prismic.io/unitelabs/Rf999kEZOvXphW50_UniteLabsmountainretreat.jpeg?auto=format%2Ccompress&rect=0%2C256%2C2464%2C1386&w=1600&h=900","UniteLabs co-Founders Lukas Bromig and Julian Willand at a company retreat",{"width":418,"height":419},1600,900,"Rf999kEZOvXphW50",{"x":26,"y":422,"zoom":38,"background":359},256,{"type":347,"text":424,"spans":425,"direction":344},"Whether you’re a scientist, platform leader, or lab automator, let’s take a first-principles approach to understanding how labs can succeed in the coming decade. Function over form.",[],{"type":427,"text":428,"spans":429,"direction":344},"heading3","A Return to First Principles",[430],{"start":26,"end":431,"type":381},28,{"type":347,"text":433,"spans":434,"direction":344},"We see four core truths to lab automation:",[435,440],{"start":436,"end":437,"type":405,"data":438},27,41,{"link_type":163,"url":439,"target":408},"https://unitelabs.io/resources/blog/what-is-lab-automation/",{"start":436,"end":437,"type":381},{"type":347,"text":442,"spans":443,"direction":344},"1. A lab exists to create data. The work is only as good as the data it leaves behind. Capture it badly, and you've paid for the experiment twice.",[444,446,451],{"start":26,"end":445,"type":381},31,{"start":447,"end":448,"type":405,"data":449},64,85,{"link_type":163,"url":450,"target":408},"https://unitelabs.io/resources/blog/lab-data-management/",{"start":447,"end":448,"type":381},{"type":347,"text":453,"spans":454,"direction":344},"2. Control and data are one thing. An instrument acts and records in the same motion, the same way a scientist does. Run them as two stacks, and you've cut the science in half.",[455],{"start":26,"end":456,"type":381},34,{"type":347,"text":458,"spans":459,"direction":344},"3. Plan science-first, build device-up. You plan an experiment goal-first, but the platform underneath has to be built the other way. Start building the platform at the instrument level, and everything above it is reusable. Start building at the workflow, and you've built for one assay.",[460],{"start":26,"end":461,"type":381},39,{"type":347,"text":463,"spans":464,"direction":344},"4. Automation has to beat doing it by hand. If it doesn't, nobody should cross over. For 20 years, most labs were right not to. That's the bar to clear.",[465],{"start":26,"end":466,"type":381},43,{"type":347,"text":468,"spans":469,"direction":344},"Now let’s look at where we are today…",[],{"type":427,"text":471,"spans":472,"direction":344},"The Current Challenge: Islands of Automation",[473],{"start":26,"end":474,"type":381},44,{"type":347,"text":476,"spans":477,"direction":344},"Every lab today is a stack of instruments that cannot talk to each other. Each instrument has its own software, and workflows are held together by one person and a pile of scripts.",[],{"type":347,"text":479,"spans":480,"direction":344},"Why? As our co-Founder Lukas Bromig says, \"Every instrument is an island because protocols are stored inside proprietary software. When you turn this into a workcell, it becomes an island on an island. Island hopping without the right infrastructure costs us time we don't have.\"",[],{"type":414,"url":482,"alt":483,"copyright":355,"dimensions":484,"id":485,"edit":486},"https://images.prismic.io/unitelabs/Baut4vtvHPBvYKoW_island-automation-16x9.png?auto=format,compress","Islands of Automation",{"width":418,"height":419},"Baut4vtvHPBvYKoW",{"x":26,"y":26,"zoom":38,"background":359},{"type":347,"text":488,"spans":489,"direction":344},"Of course, schedulers can coordinate devices, but they’re essentially blind: they know a method's name, but not what it does, let alone what it is doing right now. The cost is a maintenance nightmare and a single point of human failure.",[490],{"start":491,"end":492,"type":493},153,162,"em",{"type":347,"text":495,"spans":496,"direction":344},"What makes it even more risky is this: when only one person understands the running system (because he or she built it), then the lab’s uptime is entirely dependent on that one person.",[497],{"start":498,"end":499,"type":381},146,164,{"type":347,"text":501,"spans":502,"direction":344},"Currently, lab automation engineers live in the gap between science and software, with no canonical title, doing maintenance instead of craft, their skills locked to one vendor's tools.",[],{"type":347,"text":504,"spans":505,"direction":344},"In many cases, they didn’t choose this role: they started out as scientists who understood a particular device or vendor software better than their bench colleagues.",[],{"type":347,"text":507,"spans":508,"direction":344},"But that leaves them stuck with little room for professional growth, apart from learning another vendor’s software. We want to unblock this and give them the tools to develop their craft…",[],{"type":427,"text":510,"spans":511,"direction":344},"The Opportunity: Why Now Is the Time for Change",[512],{"start":26,"end":513,"type":381},47,{"type":347,"text":515,"spans":516,"direction":344},"For the past 20 years, lab automation veterans watched tool after tool fail the only test that truly matters: is it easier than doing it by hand? In many cases, probably not.",[517],{"start":518,"end":519,"type":381},116,122,{"type":347,"text":521,"spans":522,"direction":344},"As an industry, we should stop chasing the self-driving lab as a starting point. At UniteLabs, we’re not anti-AI, far from it. But we do think that strong foundations need to be built first.",[],"rich_text$204c59ca-d784-48a5-bc0a-6a992df16811","rich_text",{"variation":364,"version":365,"items":526,"primary":527,"id":541,"slice_type":542,"slice_label":355},[],{"tag":528,"quote":529,"author_name":533,"author_description":534,"author_image":535},"Expert insight",[530],{"type":347,"text":531,"spans":532,"direction":344},"\"Closed loops are often overhyped. They are important, but the idea that everything will run without people is misleading.\"",[],"Tom Kissling","SiLA Consortium board member",{"dimensions":536,"alt":533,"copyright":355,"url":538,"id":539,"edit":540},{"width":537,"height":537},300,"https://images.prismic.io/unitelabs/PnufJj5ON3PXwWNq_TomKissling.jpeg?auto=format,compress","PnufJj5ON3PXwWNq",{"x":26,"y":26,"zoom":38,"background":359},"quote_block$7f5f75bd-f219-484d-9146-5f46c728d2de","quote_block",{"variation":364,"version":365,"items":544,"primary":545,"id":626,"slice_type":524,"slice_label":355},[],{"content":546},[547,550,557,560,565,569,574,579,582,586,589,592,598,601,604,607,611,614,617,623],{"type":347,"text":548,"spans":549,"direction":344},"Frankly, it would be disingenuous of us to sell the promise of an autonomous lab without recognizing the bigger need for instrument connectivity, clean data, and automation reliability.",[],{"type":414,"url":551,"alt":552,"copyright":355,"dimensions":553,"id":554,"edit":555},"https://images.prismic.io/unitelabs/aCybjCdWJ-7kSWrf_AIDriven.jpg?auto=format%2Ccompress&rect=396%2C0%2C6304%2C3546&w=1600&h=900","A look inside an AI-driven lab",{"width":418,"height":419},"aCybjCdWJ-7kSWrf",{"x":556,"y":26,"zoom":38,"background":359},396,{"type":347,"text":558,"spans":559,"direction":344},"So why are we talking about the “Lab of the Future” in this manifesto? Here’s why:",[],{"type":347,"text":561,"spans":562,"direction":344},"The bottleneck moved. AI can now design hundreds of candidates in minutes, but labs still take months to validate a handful of them. The constraint is no longer the models.",[563],{"start":26,"end":564,"type":381},21,{"type":347,"text":566,"spans":567,"direction":344},"The unit economics flipped. The vision never changed; the cost of reaching it did. \"AI isn't necessarily the whole game-changer,” says Robert Zechlin, our co-Founder and CEO. “It often makes things feasible that were always possible, but too expensive to build.\"",[568],{"start":26,"end":436,"type":381},{"type":347,"text":570,"spans":571,"direction":344},"Three technology shifts arrived at once: The world now has AI that can write and debug “glue code”; Python crossed the threshold as a default coding language; and open standards like SiLA 2 made write-once-run-anywhere integrations a reality.",[572],{"start":26,"end":573,"type":381},40,{"type":347,"text":575,"spans":576,"direction":344},"It's already happening in real life: At UniteLabs, we recently helped an intern at Roche write viable methods for a Hamilton Robotics STAR liquid handler with zero training on Venus software. This is a major step forward from vendor lock-in and complexity.",[577],{"start":26,"end":578,"type":381},35,{"type":347,"text":580,"spans":581,"direction":344},"Now let’s examine the first principles we introduced above, and start building the rocket.",[],{"type":427,"text":583,"spans":584,"direction":344},"Principle 1: A Lab Exists to Create Data",[585],{"start":26,"end":573,"type":381},{"type":347,"text":587,"spans":588,"direction":344},"If a lab's product is data, then broken data isn't just an IT annoyance. It means the business is quietly failing.",[],{"type":347,"text":590,"spans":591,"direction":344},"That’s why at UniteLabs we talk about turning your lab into a “data factory”: the goal is to verify a hypothesis, and proprietary generation of science-ready data is how you get there.",[],{"type":347,"text":593,"spans":594,"direction":344},"What is science-ready data? Why are we even discussing this in the 21st century, and shouldn’t we know this as scientists? What the industry describes as FAIR data should be the minimum bar we hold our output to. If your data isn't Findable, Accessible, Interoperable, or Reusable, you just wasted most of your research budget.",[595],{"start":596,"end":597,"type":381},154,163,{"type":347,"text":599,"spans":600,"direction":344},"In an ideal world, you get full data lineage to replicate each step of a lab run as faithfully as possible, and can track samples as data-based objects in real time as they flow through your lab. Automated data acquisition, contextualization, execution and process data, the list goes on. This also means no added work for building an audit trail. We have the technology and the need.",[],{"type":347,"text":602,"spans":603,"direction":344},"Currently, however, bad data is everywhere: mismatched formats, missing context, manual steps, the data point nobody remembered to capture. Impossible to replicate or derive value from.",[],{"type":347,"text":605,"spans":606,"direction":344},"\"Bad data quietly erodes everything you measure your lab by — throughput, profitability, the value of the work itself,” adds UniteLabs co-Founder Robert Zechlin. “A lab exists to verify a hypothesis, and if you don't capture the data, the lab is worthless.\"",[],{"type":427,"text":608,"spans":609,"direction":344},"Principle 2: Control and Data Are One Thing",[610],{"start":26,"end":466,"type":381},{"type":347,"text":612,"spans":613,"direction":344},"We believe that control and data belong together.",[],{"type":347,"text":615,"spans":616,"direction":344},"Why? Think about how a scientist actually works: they run experiments and capture the context at the same time. Splitting these two things apart splits the science itself in half.",[],{"type":347,"text":618,"spans":619,"direction":344},"Today, however, automation software drives the robots and separate data software like a LIMS collects the results. Two stacks, two halves.",[620],{"start":621,"end":622,"type":381},115,137,{"type":347,"text":624,"spans":625,"direction":344},"We think labs should treat the instrument as both an actor and a data generator, and build the infrastructure to handle both at once. This turns a LIMS into a consumer of a real event stream instead of a filing cabinet, and is what makes an AI scientist possible at all.",[],"rich_text$2c7e8054-9f71-4a89-97bc-8e81a1efa0b2",{"variation":364,"version":365,"items":628,"primary":629,"id":644,"slice_type":542,"slice_label":355},[],{"tag":630,"quote":631,"author_name":635,"author_description":636,"author_image":637},"Expert Insight",[632],{"type":347,"text":633,"spans":634,"direction":344},"\"Instead of discrete handoffs between automation and LIMS, we want to intercept an event stream and treat that as what happened. So the LIMS becomes a consumer of real-world data, not a filing cabinet.\"",[],"John Whittaker","Co-Founder, LSMC",{"dimensions":638,"alt":640,"copyright":355,"url":641,"id":642,"edit":643},{"width":639,"height":639},200,"John Whittaker, LSMC","https://images.prismic.io/unitelabs/UHgKgDcOGmVUOSIF_JohnWhittaker.jpeg?auto=format,compress","UHgKgDcOGmVUOSIF",{"x":26,"y":26,"zoom":38,"background":359},"quote_block$7f9709f8-7b0d-42e9-b995-8a790ce6fbe6",{"variation":364,"version":365,"items":646,"primary":647,"id":782,"slice_type":524,"slice_label":355},[],{"content":648},[649,652,655,662,665,668,676,679,682,687,690,693,696,699,702,705,708,715,718,721,724,729,732,737,740,743,746,753,764,767,770,773,776,779],{"type":347,"text":650,"spans":651,"direction":344},"At UniteLabs, we include chain of custody and data lineage as a property of how the runtime sees the world, rather than a bolt-on feature. Because the runtime already mediates every resource access, it records lineage as a structural consequence of this approach.",[],{"type":347,"text":653,"spans":654,"direction":344},"Like time itself, liquid handling is a graph of resource state changes: every aspirate is an edge from tube to tip, every dispense goes from tip to well, every plate moves from nest to nest. The runtime just records that graph faithfully and makes it queryable:",[],{"type":414,"url":656,"alt":657,"copyright":355,"dimensions":658,"id":659,"edit":660},"https://images.prismic.io/unitelabs/aW-P0QIvOtkhBvVJ_Automate.png?auto=format%2Ccompress&rect=76%2C0%2C1920%2C1080&w=1600&h=900","UniteLabs is modular by design, and scalable by nature",{"width":418,"height":419},"aW-P0QIvOtkhBvVJ",{"x":661,"y":26,"zoom":38,"background":359},76,{"type":347,"text":663,"spans":664,"direction":344},"This means that there’s a uniform data shape across every assay, so a DNA extraction and an ELISA workflow produce the same chain-of-custody query. And it also means that because data lineage is included, clean data stops being a reason not to automate a workflow.",[],{"type":347,"text":666,"spans":667,"direction":344},"Closed-loop experiments and next-generation scheduling become possible because you can see exactly what happened on a device, then act accordingly. You no longer need to retry it five times, you can react to a specific situation based on detailed information.",[],{"type":347,"text":669,"spans":670,"direction":344},"If you're a lab leader, then good news: this approach means that execution stays on-premise, at the instrument, where regulated work must live, while orchestration and policy run in the cloud.",[671,675],{"start":672,"end":597,"type":405,"data":673},150,{"link_type":163,"url":674,"target":408},"https://unitelabs.io/resources/blog/lab-orchestration-explained/",{"start":672,"end":597,"type":381},{"type":347,"text":677,"spans":678,"direction":344},"The audit trail is part of the layer, captured the moment work happens, so there's nothing for a technician to remember to switch on. Every operator decision, every error recovery, every measurement, every plate that moved is recorded as an event on one timeline.",[],{"type":347,"text":680,"spans":681,"direction":344},"So that when an auditor asks what happened to a sample at 9:14am last Tuesday, you can show them, down to the well.",[],{"type":427,"text":683,"spans":684,"direction":344},"Principle 3: Plan Science-First, Build Device-Up",[685],{"start":26,"end":686,"type":381},48,{"type":347,"text":688,"spans":689,"direction":344},"A scientist plans science-first. This sets the requirements for the workflow you need. The device shows up late in that sequence, and that's correct.",[],{"type":347,"text":691,"spans":692,"direction":344},"Building the platform underneath to facilitate that, however, runs the other way.",[],{"type":347,"text":694,"spans":695,"direction":344},"That planning flow only works if someone did the hard part first: made every instrument speak a common, machine-readable language. Build workflow-first, and that step breaks the moment an assay or an instrument changes. Build from the device up, and it holds.",[],{"type":347,"text":697,"spans":698,"direction":344},"So start at the instrument, and everything above it is reusable. Start building at the workflow, and you've built for one assay. This approach is harder and slower at the outset. But it’s a foundation that can truly scale: instruments are how it’s built, workflows are what you get.",[],{"type":347,"text":700,"spans":701,"direction":344},"It also means there’s zero lock-in. You can integrate your own devices, bring your own hardware, and write your own methods. And with UniteLabs, everything is available as source code. There is no “black box” of impenetrability. A protocol you write today belongs to you.",[],{"type":347,"text":703,"spans":704,"direction":344},"Most automation platforms hand you a Graphical User Interface (GUI). It covers the routine cases well and stops exactly where they end. Code-based solutions like UniteLabs go beyond this to make simple things simple and hard things possible. Version control, testing, and data lineage come included. Open standards like SiLA 2 make every new integration an investment in your ecosystem.",[],{"type":347,"text":706,"spans":707,"direction":344},"\"Open standards give engineers peace of mind,” says Nadim Morhell, Automation Architect at UniteLabs. “Like the USB standard and cables: you can swap instruments and systems while relying on the same basic communication model.\"",[],{"type":414,"url":709,"alt":710,"copyright":355,"dimensions":711,"id":712,"edit":713},"https://images.prismic.io/unitelabs/aimE2geQX7-eXLkK_Labautomationsolutionsheroimage.jpg?auto=format%2Ccompress&rect=0%2C282%2C2880%2C1620&w=1600&h=900","Lab automation solutions in use",{"width":418,"height":419},"aimE2geQX7-eXLkK",{"x":26,"y":714,"zoom":38,"background":359},282,{"type":347,"text":716,"spans":717,"direction":344},"Of course, labs can start their automation journey at the device level, single workcell level, or combine multiple workcells together. The fundamentals are already there with this approach.",[],{"type":347,"text":719,"spans":720,"direction":344},"We don’t sell hardware, so we have no incentive to promote any particular instrument. With the SiLA 2 open standard, you can even integrate your custom hardware into the stack.",[],{"type":347,"text":722,"spans":723,"direction":344},"To put it bluntly: if a vendor sells robots, their “open” platform is a sales funnel.",[],{"type":427,"text":725,"spans":726,"direction":344},"Principle 4: Automation Has to Beat Doing It by Hand",[727],{"start":26,"end":728,"type":381},52,{"type":347,"text":730,"spans":731,"direction":344},"The lab of the future will feature the same workflows as before, but digitally connected, so everything done at the bench is captured as context you can actually use.",[],{"type":347,"text":733,"spans":734,"direction":344},"Lab automation must become obviously easier than doing benchwork by hand.",[735],{"start":436,"end":736,"type":493},36,{"type":347,"text":738,"spans":739,"direction":344},"Then scientists and lab automators can move up the chain of command, designing the experiments and systems that validate a design candidate in hours, not weeks.",[],{"type":347,"text":741,"spans":742,"direction":344},"This is the device-up approach paying off for the scientist: automation only beats doing it by hand if the barrier to entry drops. Today it can't. Making one workcell do everything up front means a patchwork build, and a scientist can't just specify what they need and start.",[],{"type":347,"text":744,"spans":745,"direction":344},"Often, these workcells take months to years to actually go into production. By then, the science has moved on.",[],{"type":414,"url":747,"alt":748,"copyright":355,"dimensions":749,"id":750,"edit":751},"https://images.prismic.io/unitelabs/aJstrqTt2nPbaNvY_d86d133d3bcd87589240ce140174edf158cf93d6.jpg?auto=format%2Ccompress&rect=0%2C327%2C4096%2C2304&w=1600&h=900","Liquid handling station performs mulit-channel pipetting steps.",{"width":418,"height":419},"aJstrqTt2nPbaNvY",{"x":26,"y":752,"zoom":38,"background":359},327,{"type":347,"text":754,"spans":755,"direction":344},"The future is a distributed set of capabilities. You automate the liquid handling on whatever standalone handler you have, get that part working, then pass the plate to a reader two buildings away to continue the run.",[756,758,763],{"start":757,"end":513,"type":381},16,{"start":759,"end":760,"type":405,"data":761},66,81,{"link_type":163,"url":762,"target":408},"https://unitelabs.io/lab-automation-solutions/liquid-handling/",{"start":759,"end":760,"type":381},{"type":347,"text":765,"spans":766,"direction":344},"When that works, you carry it to a different vendor's handler that sits next to the reader, with a robotic arm to bridge them. The setup evolves as the science does.",[],{"type":347,"text":768,"spans":769,"direction":344},"For automators, the skill that matters won’t be writing automation code, because agents can already do that cheaper, faster, better. It’s translating a scientist's goal into a roadmap of equipment, infrastructure, and throughput that still scales in two years.",[],{"type":347,"text":771,"spans":772,"direction":344},"As AI agents become smarter, we predict that the most important skills for lab automators will increasingly be human ones. Empathy, creativity, and critical thinking will become paramount because AI models don’t understand physical consequences in a wet lab.",[],{"type":347,"text":774,"spans":775,"direction":344},"Their career path will shift from instrument operator to workflow expert, with titles such as Head of Lab Technology or Director of Automation. This is the profile that every serious biotech company is now trying to hire for.",[],{"type":347,"text":777,"spans":778,"direction":344},"But lab automators must actively choose this path. The alternative is to deepen vendor software expertise and continue fixing glue code and broken workflows. The window of opportunity is open now. It won’t stay open forever.",[],{"type":347,"text":780,"spans":781,"direction":344},"New types of experts will soon become prevalent at serious biotechs: lab automators will be workflow architects, and scientists must team up with LLMs to get a running experiment.",[],"rich_text$df967554-07d9-4333-8557-013c7b6e21b1",{"variation":364,"version":365,"items":784,"primary":785,"id":801,"slice_type":542,"slice_label":355},[],{"tag":630,"quote":786,"author_name":790,"author_description":791,"author_image":792},[787],{"type":347,"text":788,"spans":789,"direction":344},"“Scientists need to spend less time moving samples around or reformatting data, and more time focusing on experimental design, troubleshooting, and interpreting results.”",[],"Dr. Natalia Serrano","Tecan",{"dimensions":793,"alt":795,"copyright":355,"url":796,"id":797,"edit":798},{"width":794,"height":794},679,"Natalia Serrano, Tecan","https://images.prismic.io/unitelabs/sdlYNAzlZ0Ez-Jf3_NataliaSerrano.jpeg?auto=format%2Ccompress&rect=36%2C18%2C601%2C601&w=679&h=679","sdlYNAzlZ0Ez-Jf3",{"x":736,"y":799,"zoom":800,"background":359},18,1.13,"quote_block$720eef2b-c1e6-477a-9532-1bc950afe680",{"variation":364,"version":365,"items":803,"primary":804,"id":850,"slice_type":524,"slice_label":355},[],{"content":805},[806,811,814,817,820,823,829,835,843],{"type":427,"text":807,"spans":808,"direction":344},"The New Competitive Imperative",[809],{"start":26,"end":810,"type":381},30,{"type":347,"text":812,"spans":813,"direction":344},"We believe that the labs that win over the next decade will be those that have most of their wet lab work reliably automated and can generate their own unique FAIR data at scale.",[],{"type":347,"text":815,"spans":816,"direction":344},"This data will include the full context of when a lab sample arrived, who handled it, how long it was frozen, which devices processed it, and what their specific states were when doing so.",[],{"type":347,"text":818,"spans":819,"direction":344},"Our industry’s open secret is this: advanced automation is currently a walled-garden advantage that only big pharma can afford. Democratizing it levels the field for the smaller players.",[],{"type":347,"text":821,"spans":822,"direction":344},"In this scenario, boring reliability will make future winners. Not demos, not closed-loop theater. Automation you can depend on every day, that beats doing it by hand.",[],{"type":347,"text":824,"spans":825,"direction":344},"The recent Letter of Intent shared by the SiLA Consortium asks vendors to make their instruments compatible with open standards. That's the work we do. UniteLabs is a core maintainer of SiLA 2, the standard that those pharma leaders just named and requested.",[826],{"start":827,"end":828,"type":381},167,182,{"type":347,"text":830,"spans":831,"direction":344},"We build best-in-class connectors, we help vendors adopt the standard themselves, and our Connector Development Kit (CDK) is the framework that labs like Novo Nordisk and DKMS Deutschland use to build their own.",[832],{"start":380,"end":621,"type":405,"data":833},{"link_type":163,"url":834,"target":408},"https://docs.unitelabs.io/connector-development/",{"type":414,"url":836,"alt":837,"copyright":355,"dimensions":838,"id":841,"edit":842},"https://images.prismic.io/unitelabs/yr_6TN8NPfswyr4Q_AccelerationConsortiumhackathon.jpeg?auto=format,compress","Acceleration Consortium hackathon",{"width":839,"height":840},1152,648,"yr_6TN8NPfswyr4Q",{"x":26,"y":26,"zoom":38,"background":359},{"type":347,"text":844,"spans":845,"direction":344},"In October, we're running a hackathon on our CDK with more than 120 people, and can't wait to see what they build with it. The mandate is here now, and we're ready for it.",[846],{"start":431,"end":847,"type":405,"data":848},37,{"link_type":163,"url":849,"target":408},"https://airtable.com/appYBjHgttvBuz3XR/paga3fOK3rkLzXhYc/form","rich_text$bab4a130-3452-445e-a681-e195d3ff5dd9",{"variation":364,"version":365,"items":852,"primary":853,"id":861,"slice_type":542,"slice_label":355},[],{"tag":630,"quote":854,"author_name":635,"author_description":636,"author_image":858},[855],{"type":347,"text":856,"spans":857,"direction":344},"\"It's not 'if' this is going to happen, but 'when.' I'd rather be part of the change than on the back of the bus.\"",[],{"dimensions":859,"alt":640,"copyright":355,"url":641,"id":642,"edit":860},{"width":639,"height":639},{"x":26,"y":26,"zoom":38,"background":359},"quote_block$549ecbcf-8182-46fc-b134-4e9da32f1218",{"variation":364,"version":365,"items":863,"primary":864,"id":893,"slice_type":524,"slice_label":355},[],{"content":865},[866,870,873,882,885],{"type":427,"text":867,"spans":868,"direction":344},"Join the Mission",[869],{"start":26,"end":757,"type":381},{"type":347,"text":871,"spans":872,"direction":344},"In five years, scientists and automators will be able to walk up to a lab instrument and have a conversation with it, the same way you can talk to an AI tool today. No buttons involved.",[],{"type":347,"text":874,"spans":875,"direction":344},"Lab automators will become more important than ever: as senior architects, designing the systems and workflows required to translate scientific intent into high-quality data.",[876,881],{"start":26,"end":877,"type":405,"data":878},14,{"id":879,"type":15,"tags":880,"lang":17,"slug":31,"first_publication_date":32,"last_publication_date":33,"uid":34,"url":35,"link_type":23,"isBroken":8},"abA3BxEAACIAb8C9",[],{"start":436,"end":437,"type":381},{"type":347,"text":883,"spans":884,"direction":344},"Scientists will be free to describe the workflows they want, unconstrained by vendor lock-in.",[],{"type":347,"text":886,"spans":887,"direction":344},"If you want to discover how we’re building for this, send us a message.",[888],{"start":889,"end":890,"type":405,"data":891},53,70,{"link_type":163,"url":892,"target":408},"https://unitelabs.io/company/contact/","rich_text$2b65f2bd-bf83-4843-ac1d-04a5919cd52a","'Lab of the Future' Manifesto: A Return to First Principles","The self-driving lab was oversold for 20 years. Here's our vision: connectivity, clean data, and reliability will decide which labs win. Not closed-loop theater.",1785510482779]