JobCrawls is a free job search for Finland. It collects about 20,000 open jobs from employers' own career pages and the public Työmarkkinatori into one search, with salary ranges, employer ratings and alerts, in English, Finnish and Swedish. Instead of relying on paid job ads, JobCrawls automatically indexes thousands of employers' career pages. It is free for job seekers, and employers get a free careers page. JobCrawls is a job search engine, not a recruitment agency: it does not place candidates or charge employers per hire.

Flow Intimates creates period underwear, period swimwear, and Flow Care – intimate care developed for women. We are a Danish femtech brand creating beautiful, reusable products free from PFAS and biocides, made in the EU. We are committed to increasing knowledge and awareness of women’s health – from menarche to menopause.

We're on a mission to help financial professionals (actually) use AI. We have built a Virtual Controller that helps bookeepers, accountants and controllers with ensuring they produce a high quality output for their end customers. We are a VC backed startup and more importantly have (paying!) customers. We are on a crazy ride and looking for people that want to be a part of building at the forefront of AI with us. Reach out to hear more :)

Tenol is developing a structured recruitment platform to help young candidates and local businesses solve the gap between first-job seekers and relevant entry-level job opportunities through practical matching, candidate screening and a clearer recruitment process. Many young people struggle to get their first job, not necessarily because they lack motivation, but because the path into work is unclear. They often do not know where to start, how to present themselves, or how to become visible to employers. At the same time, many businesses need motivated people for full- or part-time roles, extra help, weekend shifts and practical tasks, but do not always have the time or structure to find and assess young candidates properly. This creates a gap between young people who want to work and businesses that need help. Tenol is focused on making that connection easier, safer and more structured. Tenol helps candidates register their interest, availability and profile in a structured way. Businesses can describe their needs, such as role, working hours, requirements and preferred candidate profile. Tenol then works to match candidates with relevant opportunities based on practical fit, including availability, motivation, role requirements and communication. Instead of only forwarding names, Tenol aims to provide businesses with clearer candidate shortlists and structured candidate presentations. The goal is to reduce friction for businesses while giving young candidates a more professional and understandable path into working life. The motivation behind Tenol comes from seeing how difficult the first step into working life can be for many young people. A lot of candidates are motivated, but they are not always given a clear or fair way to show it. At the same time, businesses often need reliable help, but the process of finding young candidates can be time-consuming and unstructured. Tenol was started because this connection can be better. First jobs matter. They build confidence, experience, responsibility and future opportunities. Tenol exists to make that first connection between candidate and employer more practical, structured and human.

Costile is an AI agent diagnostic proxy for teams building production AI workflows. As companies start using AI agents for support, research, coding, internal operations, and automation, they run into a new kind of infrastructure problem: the agent may technically work, but nobody knows when it is wasting money, looping, retrying badly, using the wrong model, or silently drifting outside expected cost behavior. Most teams can see their total AI bill after the fact. That is too late. What they need is operational visibility into which agent caused the spend, what pattern caused it, how severe it is, and what action should be taken. Costile sits between a company’s AI agents and model providers such as Anthropic. It routes requests through a proxy, logs only metadata such as model, tokens, cost, timestamps, agent ID, session ID, and stop reason, and turns that metadata into diagnostics. Prompts and responses are not stored. The product shows teams a command-center view of their AI agents: which agents are healthy, which are critical, what they spent in the selected time window, and what issue is driving the risk. When an agent is flagged, Costile gives a diagnostic report with the incident window, request log, baseline comparison, projected monthly exposure, and recommended fix. The problem we are solving is not just “AI is expensive.” The deeper problem is that AI agents are becoming autonomous software systems, but companies are still monitoring them like simple API calls. A bad agent loop, retry cascade, model-routing mistake, or runaway request can create cost, reliability, and governance risk before anyone notices. Costile helps engineering, product, and operations teams answer three questions quickly: What is going wrong? Which agent or session caused it? What should we do now? The initial product focuses on AI cost diagnostics, haywire detection, alerts, audit logs, API key management, and enterprise-ready reporting. Over time, Costile can become the observability and control layer for AI agent operations.

Teton is a care empowerment platform for senior living and healthcare operators. We use an in-room sensor and application layer to continuously understand residents, staff activity, and the care environment, then translate those signals into action for frontline care teams. Senior care operations are under structural pressure. Chronic staffing shortages, rising resident acuity, and inconsistent observational data have left care teams flying blind between documented events. Most existing tools simply record what already happened, and that is no longer sufficient. When teams are stretched, they need earlier signal, faster response, and more consistent decision-making, not another retrospective report. Teton exists to close the decision gap between observation and action. The shift we are making is from a reactive model of documentation, isolated alerts, manual interpretation, and delayed intervention, to a proactive one built on earlier signal, workflow-aligned insight, and faster, more consistent action. Our direct user is the care team, and resident and family outcomes improve because staff decisions improve. What sets us apart is that we lead with outcomes and let the technology serve them, not the other way around. We provide continuous visibility that surfaces risk before situations escalate. We fit into existing care workflows without adding new steps. We use longitudinal behavioral and health signals like movement, gait, sleep, and routine patterns to enable individualized, preventative care rather than one-size-fits-all responses. And we deliver community-level operational clarity from consistent in-room data, supporting accountability without resorting to surveillance or long-buffer video watching. Importantly, Teton is not a fall detection product, a single-event alerting system, or a retrospective dashboard. Those tools address fragments of the problem. We address the whole gap. The reason this matters is that when care teams can see risk sooner and act earlier, the impact compounds. Operators see stronger resident retention through more consistent and individualized care, lower incident-related costs by reducing preventable falls and hospitalizations, improved staffing efficiency by removing manual observation and rounding burden, and greater operational predictability across shifts, teams, and communities. Care quality stops depending on which staff member or which shift happens to be working. Our north star is simple: Teton empowers care teams to stay one step ahead, so operators can deliver better outcomes and run more predictable businesses. Stay Ahead. Care Ahead.

Patent pending deep tech innovations in drone fleet /swarm operations by bringing autonomous aerial infrastructure. https://www.linkedin.com/company/sentinel-fleet-ai https://sentinelfleet.ai/ About Sentinel Fleet Sentinel Fleet is creating a new category: Autonomous Aerial Infrastructure. While the drone industry has focused on aircraft, sensors, and missions, the infrastructure required to scale autonomous operations has remained largely unsolved. We are building that infrastructure. The Missing Infrastructure Layer Autonomous systems cannot scale on manual infrastructure. Our patent-pending platform combines intelligent docking, power management, fleet coordination, and autonomous operations into a single system that enables drones to operate continuously with minimal human intervention. The result is a network that transforms drones from isolated tools into persistent, coordinated assets capable of delivering real-world outcomes at scale. Deploy anywhere. Scale effortlessly. Operate continuously. Autonomous Intelligence AI turns a network of drone docks into an autonomous sensing and response system. It continuously deploys, coordinates, and recharges drones while analyzing data at the edge in real time. This enables persistent monitoring, faster decisions, and lower operational costs without human intervention.

Vexter hjelper B2B-selgere å jobbe smartere ved å kombinere presis prospektdata med et intelligent AI-verktøy for e-post outreach. Vi gjør det enkelt å finne riktige leads, bygge målrettede kampanjer og skape flere møter på kortere tid. Med Vexter bruker du mindre tid på manuelle prosesser og mer tid på å selge. Plattformen omsetter data til innsikt som øker konverteringsraten, øker effektiviteten og skalerer veksten.

Asenti uses AI to review construction project documents and detect errors, inconsistencies, and missing information before they cause problems on site. By improving quality control early in the process, we help construction teams reduce costly mistakes, avoid rework, and improve coordination across disciplines.

Velocity Insights is building a new class of analytical production systems that generate decision intelligence from a fully traceable evidence base. Most commonly used GenAI approaches generate narratives first and attempt to justify them during the text generation process — often resulting in outputs that are incomplete, difficult to verify, and not fully traceable to underlying evidence. Velocity Insights takes a different approach, structuring the evidence first and deriving every insight from it. This enables organizations to produce analytical outputs that are fully traceable, inspectable, and auditable — transforming how conclusions are validated in high-stakes decision environments. Designed for capital allocation and strategic decision-making, Velocity Insights enables enterprises across finance, life sciences, and technology to generate high-speed decision intelligence without sacrificing traceability or control. By combining data structuring, workflow design, and AI, the system establishes a new standard: analytical outputs that are fully verifiable, transparent, and trusted.

Many industries struggle with the same core problems: • Existing solutions are often expensive, complex, or limited to specific product types. Our solution is a security . The technology is simple, scalable, and does not require changes to existing logistics product authenticity and return control matter.

Kihleo is a medtech startup developing an early warning system for urinary tract infections in older people with incontinence receiving care at home or in nursing homes. UTIs are one of the most common reasons for acute deterioration, confusion, and hospitalisation in this group. They are challenging to detect early, because symptoms are often vague, many older people cannot clearly communicate discomfort, and home care staff and nurses have minimal time. Today, detection is primarily reactive. Staff notice that something is wrong, then order urine tests and start treatment when the infection is already well underway. This leads to unnecessary suffering, avoidable admissions, and a high use of antibiotics. Kihleo’s solution is a small sensor placed in the diaper that measures biomarkers in the urine every time the person voids. When the diaper is changed, the sensor is read, and data is sent to a secure backend. Algorithms and predictive models analyse patterns over time and provide early, trustworthy indications that an infection may be developing, days before clinical symptoms are usually recognised. The system is not a diagnostic tool. It is a decision-support and early-warning system that integrates into existing workflows and helps staff decide when to look more closely, consult a nurse or doctor, and perform standard diagnostic tests. The value is threefold. For older people, it means faster and more targeted treatment, fewer severe infections, less confusion, and a better day-to-day quality of life. For relatives and care staff, it provides reassurance, objective data, and more time for actual care rather than crisis management. For the public sector, it helps prevent avoidable hospitalisations and complications that are both expensive and resource-intensive. Kihleo is working with a hardware partner on sensor development and is already in dialogue with Danish municipalities about pilot projects. The long-term vision is to create a scalable, data-driven platform for early detection of infections and other complications in elderly care, using everyday materials like diapers as non-invasive data sources.

The live entertainment industry still runs on analog processes,scattered Google Docs, Excel sheets, and manual workflows.” Jocky is building the digital infrastructure for live entrainment. Collecting Invoices, scheduling, booking and live entertainment data so that venues, artists, and agencies can run their operations from a single place.

Only 7.9% of new medicin is approved for phase 1 clinical programs - life saving cures are being scrapped because of poor reproducibility. Today, researchers designing complex in vitro and in vivo experiments jump between many tools that do not talk to each other. Protocols are written in free text, naming is inconsistent, raw data is scattered across drives, and inventory and cell banks are tracked separately. This makes it hard to reproduce experiments, compare results across projects, trace which cell material went into which batch, and satisfy regulatory expectations. Small and mid-sized labs often cannot afford enterprise platforms like Benchling or Dotmatics, so they manually glue everything together and rarely get to use advanced analytics or AI. BioPilot solves this by standardising the full early-to-in-vivo CTR pipeline in one product. Users can register and template in vitro experiments (differentiation, expansion, cryopreservation, device testing, etc.) and in vivo studies (animals, groups, dosing, housing, ethics documents) using fixed ontologies. This gives every experiment a structured schema and a precise schedule of readouts, barcodes and data types to collect. Raw data (FACS, scRNA-seq, imaging, counters, bioreactor logs, etc.) is then automatically linked back to the right experiment, condition and sample. On top of this, BioPilot offers: • Inventory and cell bank tracking that makes it trivial to trace which vial, edit or expansion batch was used where. • Live bioreactor monitoring with alarms (email / phone) to prevent losing expensive batches. • A growing library of free analytical tools, including automated FACS gating, scRNA-seq pipelines and image analysis that can feed results straight back into the experiment records. • A global ontology service for vendors, instruments, cell lines, species and process terms, with a roadmap for a public API. Because everything is structured and queryable, BioPilot makes it much easier to compare experiments, run Bayesian optimisation on process parameters, and let AI suggest next-step experiments. The pricing is kept aggressively low (free tier plus a simple paid tier based on storage), so smaller biotech and academic groups can access capabilities that are normally reserved for organisations with large software budgets. In short, BioPilot aims to become the operating system for cell therapy R&D: a single, affordable platform where experiments are planned, executed, monitored and analysed in a way that is standardised enough for automation and flexible enough for real-world biology.

Homeswap is a platform where members can stay in each other’s homes instead of paying for accommodation. The model is built on credits: you earn credits when you host other members, and you use those credits to travel. There is no money exchanged between members, which makes the experience feel more personal, fair and community-driven than traditional renting. Travel with Homeswap feels different because you stay in real homes, in real neighbourhoods, from real people. It attracts a type of traveller who values meaning and connection over pure convenience. Many members also like the sustainable aspect – instead of building new hotels or keeping second homes empty, existing space is shared and used better. The platform has already grown organically to members in more than 20 countries. We have not relied on paid marketing so far. Growth has come through word of mouth, community recommendations and people who like the idea of travelling without paying for accommodation.