Technological advances have created the foundation for an increasing number of tech startups seeing the light of day. These startups are working with innovation in an organization and situation that is radically different from big companies, which has traditionally been the primary forces in high tech innovations. This has created a need for new theoretical and practical frameworks to manage innovation, which accommodates the uncertain reality experienced by startups. In the last couple of years the need has been answered by startup literature such as ‘Lean Startup’ and ‘The Startup Owner’s Manual’. This project seeks to find relevant theories and methods to manage innovation in the tech startup Spiio. Some of the most popular startup literature is reviewed and compared to acknowledge findings from innovation studies in science, technology and sociology (STS). The report finds that there is good alignment between the suggestions from STS and the reviewed startup literature. A few suggestions is made to enhance the startup literature with STS findings for considering and manipulation relevant actor-network configurations. Spiio is then analyzed using key findings from the reviewed startup literature and STS. First part of the analysis results in identifying a misalignment in the actor network and a new configuration is proposed to align interests and create stability. A strategy for establishing the new configuration was first formulated and subsequently executed with success. In the last part of the report a business model analysis is carried out using methods and frameworks from the startup literature. The analysis identifies a series of knowledge gaps in Spiio’s business model. Resulting from this suggestion is made for a number of areas, which Spiio should prioritize.