We build generative AI applications that create, summarise, search, and act — grounded in your data, measured for quality, and integrated into the tools your teams already use. From GenAI search to domain copilots, we ship systems operators can trust.
GenAI delivery for startups and enterprises across India, USA, UAE, Germany, Australia & more.
Generative AI earns ROI when it is embedded in workflows — drafting with citations, generating structured data, powering multilingual content, or answering from private knowledge. We design GenAI features as product surfaces with permissions, audit logs, and evaluation — not free-form chat alone.
We work with leading foundation models and open-source options, vector databases, orchestration frameworks, and your cloud of choice. Model choice is secondary to retrieval quality, prompt design, tool use, safety policies, and cost control — those are what we optimise for every engagement.
Knowledge assistants for support and operations, GenAI product search for eCommerce and public services, document intelligence for back-office teams, and copilots inside SaaS products. Multilingual generation and Indic-language support are first-class, not afterthoughts.
Prioritise workflows with clear owners, data access, and success metrics (deflection, time saved, conversion).
Decide how generation is grounded — RAG, tools, structured outputs, or hybrid — and build evaluation sets early.
Ship GenAI inside your UX with auth, feedback, and analytics so teams can adopt and improve it.
Expand models, languages, and channels once quality and cost are stable under real load.
We ship features users adopt, not model demos for board slides.
Deep experience combining retrieval and generation (Tensor Search lineage).
English plus Indic and other languages for real user bases.
It is the design and engineering of software that uses large generative models to create text, code, speech, or structured outputs — typically grounded in business data and integrated into products or workflows.
GenAI systems need evaluation for hallucinations, retrieval design, safety policies, and ongoing cost control. We build those operational concerns into the delivery, not as an afterthought.
We are model-agnostic. We select commercial APIs or open-source models based on accuracy, latency, data residency, and cost for your use case.
Yes. We typically use RAG and secure integrations so models answer from your private sources without training on your data unless you explicitly choose fine-tuning with clear controls.
Tell us the workflow. We will propose architecture, timeline, and a pilot plan you can take to stakeholders.
Book a free 30-minute consultation. We'll map the fastest path from concept to a production-ready product.