Vector runs open-weight models like Gemma on your own hardware, even fully air-gapped. It learns from your documents, becomes your own model, and shows every rule you must follow in every country and state you operate in.
Scanned files, records, policies and rule books go in as they are. Cited answers, drafts and audit-ready compliance come out, from a machine that never talks to the internet.
Every organization gets an internal AI that knows its work, running on physical AI it controls: a machine inside its own building.
Your own model, built on open weights and shaped by your documents, your approved answers and your rules.
The hardware your AI runs on, inside your walls: a laptop for a demo, a server room for production, GPUs when you need them.
Vector and Ollama run on a machine you own. No cloud account, no outbound connection.
Upload policies and procedures, tag them by department, and choose which ones the AI answers from and learns from.
Start with Gemma. Add or swap open-weight models as they improve; nothing is locked in.
Your model drafts examples from your documents, people approve them, and a new version of your own model is built and evaluated.
Staff get cited answers and task-specific applications, each with a clear rule for who reviews the output.
See readiness by country and state, the probable loss if a rule is ignored, assign the work and print the report.
Patient data stays inside the hospital network. One private platform serves clinical, operations, billing, compliance and research teams, with role-based access, audit logs and human approval where it matters.
Choose your service area and where you operate. Vector already knows the rules: international standards, national law, state or provincial law, local and board rules, and your own policies. It checks every document against them, shows what is done and what is pending, and estimates the probable loss if a rule is not complied with.
Probable loss is an illustrative model (exposure estimate × likelihood by status) built from statutory figures, meant to be replaced with your own estimates. Rule lists are a starting set to confirm with counsel; you add your own. Examples in small text show how a layer looks in one place; the same structure applies wherever you operate. Each industry has its own checks, and results depend on the documents each organization uploads.
Models, documents, prompts and answers stay on your hardware. Air-gapped installs are supported.
Evaluations, training data and model versions are yours, built from your work and portable.
Gemma today, any open-weight model tomorrow. Change models without changing your workflows.
Obligations by industry and place, evidence, tasks, probable loss and printable reports.
Every action is a block in a SHA-256 hash chain, written in plain sentences: who did what, when.
Departments, roles and permissions decide who sees which documents and which AI answers.
A 30-minute session with the Vector team, built around your environment and your rules.
Vector builds the infrastructure for organizations to own their AI: deployed on hardware they control, connected to their knowledge, adapted to their work and compliant with the rules of every place they operate.
Every deployment runs on the customer's own servers with open-weight models, and no request goes to an external AI API. Compliance checks differ by industry and are run against each customer's own uploaded documents.
Vector built and runs our examination and convocation systems on the university’s own servers, and they’ve handled our students’ payments without a hitch. Their AI evaluation tool and document-based NAAC compliance checks have changed how our offices prepare for accreditation. What matters most to us is that student data never leaves the campus.
We needed AI that understood University of Mumbai and national education rules, not a generic chatbot. Vector checks our documents against those rules and tells us exactly what is pending and who owns it. Their student evaluator has also saved our faculty real time. It was set up on our premises with very little effort from our side.
Client confidentiality is non-negotiable for a law firm, so cloud AI was never an option for us. Vector built our entire system in-house, with agents for research, scheduling, drafting and compliance, and it runs inside our office. We’re testing it internally now, and it already covers work that used to take hours.
Running an emergency hospital in Mumbai means a long list of national and state compliance requirements. Vector checks our documents against all of them, assigns the gaps to our staff, and keeps a tamper-proof record of every step. Patient data stays inside the hospital, which is what made this possible for us.
25+ years in academic governance, examination reform and accreditation. NAAC Assessor, AICTE member and quality controller for SWAYAM/NPTEL; 75+ publications, chapters and patents; Rajiv Gandhi Gold Medal; shortlisted for the QS Reimagine Education Award.
A 30-minute session: we walk through documents, models, fine-tuning, internal chat and compliance for the places you operate, then scope your first deployment.
Pick a time that suits you. Calendly sends a confirmation and a calendar invite.
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