Nsoffice
Written by the Bee, read it before you send it
KPIMore first meetings turn into real deals, on less preparation time
selling on-prem storage
Tech Data just signed an exclusive VAD partnership with Wind River (announced October 2025) covering virtualization, HCI, and container management — infrastructure categories directly relevant to how you'd host and govern data behind your 100+ connectors.
IT product distribution: infrastructure, networking, software, and hybrid cloud hardware high
Scaling NSOffice.AI beyond its 22 enterprise customers onboarded since launch
Bhargav Petla
Ai-fication Specialist at Network Science (team behind NSOffice.AI) · Not publicly specified; prior roles include AI Consultant at Network Science and time at Dell Technologies, Orion Square, and Verzeo
Bhargav Petla works on Network Science's NSOffice.AI product team and was named among the core team credited at the product's public unveiling at DTIA 10.
- Scaling NSOffice.AI beyond its 22 enterprise customers onboarded since launch
- Driving adoption of the platform's 100+ system connectors across finance, sales, ops
- Positioning NSOffice.AI as a sovereign, governed alternative to unmanaged 'shadow AI' use
- Supporting enterprise data residency, encryption, and RBAC requirements for buyers
- Building out integrations spanning ERP, CRM, HRMS, BI, and document/storage systems
- Enterprise AI governance and 'shadow AI' risk
- Multi-LLM orchestration and contextual intelligence
- AI-native enterprise productivity tools
- Network Science company culture and team offsites
- Deep tech (AI, ML, robotics, IoT) innovation
Colleague post crediting Bhargav Petla among the team behind NSOffice.AI's DTIA 10 unveiling
NSOffice.AI framed around 'Shadow AI' and giving employees a trusted, governed AI version
Team offsite post referencing content created 'using NSOffice.AI'
Nsoffice today
- Industry
- Enterprise AI software / AI productivity platform
- Size
- Small startup team; product has onboarded 22 enterprise customers since launch
- HQ
- London, England (registered office, 30 Churchill Place, E14 5RE); parent Network Science has India presence (Mumbai)
- Footprint
- UK (registered entity) · India (Network Science team, Mumbai) · Serves global enterprise customers
NSOffice.AI is an AI-native enterprise productivity suite built by Network Science, offering a single "Ask Bar" that unifies search, automation, and analysis across 100+ connected business systems (ERP, CRM, HRMS, BI, storage). It positions itself as a governed, private alternative to ad hoc "shadow AI" tool use, emphasizing data sovereignty, RBAC inheritance, and encryption for enterprise buyers.
- NSOffice.AI Ltd incorporated in the UK on 6 March 2026, per Companies House filing
- Product publicly unveiled at industry event DTIA 10 (per LinkedIn recap, late 2025/early 2026)
- Introductory product video published on YouTube, dated May 20, 2026
- Reported 22 enterprise customers onboarded since launch, per BOLD Awards project page
- Site messaging states executives spend '23 hours weekly hunting across systems' for known information
- Enterprise page flags employees sharing sensitive data with LLMs 'discretely' creating visibility/compliance gaps
- Product must integrate with heterogeneous existing 'Document & Storage' systems without rip-and-replace, per site claim
- Committed to a connector-based, no-rip-and-replace integration model across ERP, CRM, HRMS, BI, storage (100+ connectors)
- Publicly commits to GDPR compliance, data residency, and 'never used to train AI models' data policy
- Positions itself against unmanaged shadow AI with a sovereign, governed enterprise AI offering
Positioning
Tech Data gives you on-prem storage infrastructure with the integration, financing, and lifecycle support to plug into your existing ERP, CRM, HRMS, BI, and storage connectors without ripping anything out. As a multi-vendor distributor with 2,500+ vendor relationships, we can match the exact storage class you need for enterprise-grade data residency and RBAC-consistent deployments.
Conversation arc
“Bhargav, congrats on the DTIA 10 unveiling — I want to talk about the storage layer sitting behind NSOffice.AI's 100+ connectors as you scale past your first 22 enterprise customers.”
“Walk me through how you're currently handling document and storage system integrations for enterprise buyers who won't rip out their existing infrastructure.”
“We distribute on-prem storage and hybrid cloud hardware plus integration and financing support, so you can onboard enterprise customers with data residency and RBAC requirements without building infra procurement in-house.”
“I hear you — with a small team, procurement bandwidth is thin, which is exactly why our pre-sales and financing support exists so you're not managing vendor relationships directly.”
“Can we set up 30 minutes with our storage specialists to map your connector roadmap against a couple of on-prem configurations for your next enterprise rollout?”
Ask these
- Q1When enterprise customers require you to inherit their existing RBAC rather than layer on new access controls, what storage infrastructure are they typically running underneath?
- Q2As you push past your first 22 enterprise customers, is your document and storage connector integration work being done on standard on-prem hardware or something bespoke per customer?
- Q3Given the site's commitment to data residency and 'never used to train AI models,' are your enterprise buyers asking for storage that sits in-country or on-prem specifically?
- Q4With multi-LLM orchestration across GPT-5, Gemini, Claude, O3, and Flux, how is the underlying data storage layer keeping pace with that model diversity?
Feasibility
What they appear to run
- BOLD Awards project page states platform provides 'multi-AI access across 10+ leading models such as GPT-5, Gemini, Claude, O3, and Flux'
- Site lists 100+ connectors spanning ERP, CRM, HRMS, BI, Communication, Document & Storage, Supply Chain, Custom APIs
- Enterprise page states product 'inherits your organization's existing role-based access control' rather than adding new layers