LinkLabs undertakes business and technical research across artificial intelligence, human-centered systems, audio intelligence, innovation strategy, and applied technology design. This sector exists to support clients and internal initiatives that require structured analysis, conceptual depth, and serious output quality. It is also where our products started: PitLane, Loov, and Talgud each began as research into a problem we kept meeting in delivery work.
Our research work focuses on practical relevance. We develop frameworks, evaluate technical possibilities, structure evidence, and create material that can support products, publications, innovation programs, and strategic decision-making.
Research outputs can support executive review, publication, investor discussions, technical concept definition, and product direction. The objective is clarity, defensibility, and usefulness.
The working system behind the audio intelligence thread. echoDNA turns a short voice recording into a speaker match and an emotional tonality reading, and it exists so the research above is testable against real audio rather than argued on paper.
The peer reviewed work on emotionally safe learning spaces asked whether the acoustic character of a room and the voices in it can be read well enough to support inclusive teaching. echoDNA is the engineering answer to that question: the same feature set, implemented as a service that can be pointed at arbitrary audio.
A C++ analysis engine does feature extraction and matching, a Python service carries the model inference, and a React front end drives the capture. It runs on our own AWS account in Mumbai, reached over a Cloudflare tunnel, with no third-party audio processing in the path.
The demo records a short sample in the browser to build a voice profile, then analyses further recordings against it. Audio is processed on LinkLabs infrastructure and is not shared with third parties.
Three research modes we are set up to run, either as a standalone engagement or as the analytical layer underneath a consulting or engineering programme.
Market framing, strategic analysis, innovation narratives, and decision support for new products, sectors, and venture opportunities.
Technology scans, architecture comparison, feasibility exploration, and framework definition across AI and systems domains.
Reports, publication-ready structures, concept papers, and executive-facing material for serious external audiences.
Research at LinkLabs stays close to hardware and to running systems. This is the working portfolio that keeps the firm current on the platforms our clients depend on, and it is where product ideas are pressure tested before they become products.
How much of a platform failure can be established from evidence already present in a capture, and how to make a model reason over that evidence without ever handling the raw artefact. This thread became PitLane.
Where autonomous agents can be trusted inside a regulated engineering process, and where a hard boundary has to be enforced in the system rather than requested in a prompt. This thread became Loov.
Acoustic analysis, fingerprinting, and classification, including the human-centered work behind our peer reviewed publication on emotionally safe learning spaces. This thread became echoDNA.
Vision models running continuously on embedded accelerators, where the interesting constraint is sustained operation, thermals, and cost per stream rather than a benchmark figure.
What a familiar software experience should become on a very wide, partly non touch, partly shared in-vehicle display, and how far an existing engine can be taken before it needs rebuilding.
Discovery, control, and mirroring across mixed and multi homed networks, and the class of defects that only appear once a device has more than one route to the world.
We structure research so the output ends in a decision, a specification, a publication, or a product, rather than in a document that gets circulated once.
