Seclore ARMOR AI-DLP
ARMOR AI-DLP controls sensitive data in real time at the AI interaction layer — block, redact or tokenise sensitive data in prompts before it reaches ChatGPT or Copilot, and control it in AI responses — so employees use AI without leaking data.
Buy through TechBag
Same software. Better outcome — at a lower cost.
How it’s rated
Full scoreboard ↓Quick answer
The Seclore platform family
This page covers ARMOR AI-DLP — the AI-control layer. The rest of the Seclore ARMOR platform:
Quick facts
30-second orientation- Product
- ARMOR AI-DLP — DLP at the AI layer
- Vendor
- Seclore (Mumbai · IIT Bombay-incubated · ~2008)
- The category
- AI Data Loss Prevention (AI-DLP)
- The core
- Control sensitive data flowing to & from AI
- The problem
- Employees leak data into ChatGPT/Copilot; AI exposes data
- The mechanism
- Bi-directional tokenisation/masking at the AI point
- Covers
- Public chatbots, enterprise copilots, custom AI/agents
- The benefit
- Use AI productively without leaking data
- Platform
- The AI-control layer of Seclore ARMOR
- In India via
- TechBag — licensing, quotes, GST invoicing, support
Understand AI data loss prevention before you buy it
Most product pages skip this. We start here — so you buy a capability, not a buzzword.
What is ARMOR AI-DLP?
DLP for the AI era — control sensitive data in real time at the AI interaction layer, so employees use AI without leaking data.
AI leaking data vs controlled AI usage — the honest table
What consolidation actually replaces, dimension by dimension.
| Dimension | Unprotected / signature email | ARMOR AI-DLP (Seclore) |
|---|---|---|
| Data pasted into AI | Leaks, unseen | Tokenised/masked/blocked |
| Traditional DLP + AI | Blind to the AI layer | Controls prompts & responses |
| Copilot over-exposure | AI surfaces sensitive data | Response control |
| The AI dilemma | Ban (lose value) or allow (risk) | Enable safely |
| Shadow AI | Invisible leakage | Surfaced & controlled |
| Protection direction | One-way at best | Bi-directional |
| AI usage visibility | None | Seen & audited |
| DPDP + AI | Personal data leaks to AI | Controlled & evidenced |
AI-DLP enables safe AI adoption — control the data, not the tool. Bi-directional control addresses both leakage IN and Copilot over-exposure OUT. It's a new category; TechBag positions it. Seclore is India-origin.
The five pieces of the platform
Vendors love diagrams; buyers need to know what they’re actually operating. Here’s the whole platform, demystified.
Inspect at AI Layer
Inspect data at the AI interaction point — the prompts employees send to AI and the responses coming back — the layer traditional DLP can't see, where AI data leakage actually happens.
Detect Sensitive Data
Detect sensitive data in AI interactions in real time (customer records, source code, financials, personal data), going to or coming back from a model.
Control Inbound
Block, redact or tokenise sensitive data in prompts before it reaches the AI model, with bi-directional masking, so it doesn’t leak to AI providers.
Control Outbound
Control sensitive data in AI responses too, so assistants connected to company data, like Copilot, don’t surface it to people who shouldn’t see it.
Enable AI Safely
Let employees use public chatbots, enterprise copilots, custom AI apps and agents productively while preventing sensitive-data leakage.
Track who opens sensitive data and where it lives on one map — risk contained at its starting point, not the edge.
Twelve capabilities. See, control, enable.
AI-DLP controls sensitive data flowing to and from AI — tokenised, masked or blocked, bi-directionally — the AI-control layer of the Seclore portfolio.
AI Interaction-Layer Inspection
Inspect prompts going in and responses coming out, the AI interaction layer that traditional DLP can’t see.
Real-Time Sensitive-Data Detection
Detect personal data, customer records, source code and financials in AI interactions in real time, not after the fact.
Public, Enterprise & Custom AI
Cover public chatbots (ChatGPT, Gemini), enterprise copilots (Microsoft Copilot) and custom AI apps and agents.
Bi-Directional Tokenisation & Masking
Tokenise or mask sensitive data before it reaches the model and control it in responses, so the AI works without raw data.
Block, Redact or Allow by Policy
Policy-based controls block sensitive prompts, redact sensitive parts, or allow with conditions, per your rules.
Control Data in AI Responses
Control sensitive data in responses, so assistants like Copilot don’t surface it to unauthorised people.
Shadow-AI Awareness
Help surface and control the shadow AI tools employees adopt without approval, so data doesn’t leak to unknown AI.
Enable AI, Don't Just Block It
Let employees use AI productively instead of banning it, with controls that protect sensitive data along the way.
AI-Usage Visibility & Audit
See which sensitive data flows to which AI and what is blocked or tokenised, with an audit trail for governance.
AI Compliance & Data Protection
Support compliance with India’s DPDP and GDPR by keeping personal data out of AI systems and evidencing control.
AI, Browser & Endpoint Integration
Integrate at browsers, endpoints, enterprise AI platforms and custom apps, and connect with DSPM and EDRM.
The AI-Control Layer of ARMOR
The AI-control layer of Seclore ARMOR, working with DSPM, Data Classification and EDRM for data security in the AI era.
Watch Seclore ARMOR in action
The overview, getting started, and the core workflows.
How Seclore ARMOR Works
The ARMOR data-security platform.
Where Seclore Belongs in Your Data-Security Framework
Seclore across the data-security stack.
Want a live, India-context walkthrough for your environment?
Book a guided demo →Perimeters leak. Govern the data itself.
Here’s what genuinely sets Seclore ARMOR AI-DLP apart.
AI adoption is leaking your sensitive data — right now
Employees paste customer data, source code and confidential documents into ChatGPT and copilots, and that data can end up logged or in training beyond your control. Traditional DLP doesn’t see prompts and responses. Seclore AI-DLP controls sensitive data at the AI interaction layer, so staff can use AI without leaking it.
Control at the AI layer — what traditional DLP can't do
Traditional DLP inspects files, email, endpoints and network, but not the prompt-and-response flow of AI tools, so AI is a blind spot. Seclore AI-DLP inspects data at the AI interaction point in real time, tokenising, masking, blocking or redacting sensitive data in prompts and controlling what comes back in responses.
Embrace AI's productivity — without banning it
Banning AI loses its productivity and drives usage into shadow AI; allowing it unchecked leaks data. Seclore AI-DLP controls the data, not the tool: it tokenises, masks or blocks sensitive data in prompts and controls responses, so staff use ChatGPT and Copilot while customer data and source code stay protected.
Two-way protection — including the Copilot over-exposure problem
Assistants like Microsoft Copilot inherit over-broad permissions, so they can surface salaries or confidential files a user technically can reach but should not see. Seclore AI-DLP controls sensitive data in responses as well as prompts, and with Seclore’s DSPM and EDRM tackles this over-exposure end to end.
Purpose-built for AI, from a data-security specialist and platform
AI data security is a data-security problem, and Seclore has 15+ years of data-centric expertise. AI-DLP is part of the ARMOR platform: DSPM finds what data AI can reach, Data Classification labels it, EDRM protects it and AI-DLP controls it at the AI layer. Seclore is based in Mumbai with IIT-Bombay roots.
The honest scope
Seclore ARMOR AI-DLP controls sensitive data in prompts and responses across chatbots, copilots and custom AI. The category is new and crowded, with DLP, CASB/SSE and AI-security vendors adding controls, and no vendor fully mature. Seclore’s edge is bi-directional control, the ARMOR platform and India origin.
The numbers behind the platform
What your Seclore AI-DLP journey looks like
AI data-risk scoping
Map how employees use AI (chatbots, Copilot, custom AI), which data is at risk, and your DPDP drivers. TechBag scopes it.
Deploy AI-layer control
Deploy AI-DLP at browser, endpoint and enterprise AI, set tokenise, mask or block policies, and start controlling data.
Both directions + Copilot
Tune inbound and outbound controls, including Copilot over-exposure, and connect with DSPM and EDRM.
Govern & scale
Use AI-usage audit for governance and DPDP evidence, and extend across the organisation. TechBag models it in INR/GST.
The review scoreboard
Modelled on Gartner Peer Insights structure. *Counts and breakdowns are illustrative pending verified review collection.
Quick poll — what’s driving your evaluation?
Talk to an advisor“Staff were pasting sensitive data into ChatGPT unseen. AI-DLP tokenises it before the model, so they get help and we don’t leak.”
“Controlling what Copilot reveals, not just what goes in, was the deciding factor in rolling it out safely.”
“We didn't want to ban AI — the productivity is real. AI-DLP let us enable it safely across the company instead of driving it into shadow AI.”
“Securing AI data is a data problem, so a data-security specialist mattered, and DSPM and EDRM made it a real strategy.”
“It’s a new, fast-evolving category, but bi-directional control and the platform fit made Seclore right for our AI risk.”
“For DPDP, preventing personal data leaking into third-party AI was essential. AI-DLP gave us that control and the audit trail to prove it.”
“India origin, local support and DPDP-awareness mattered as we adopted AI, and control at the AI layer works.”
“With DSPM and EDRM we discover what AI can reach, control it at the AI layer and protect the data, end to end.”
Where everyone sits — the grids
Analyst firms bury this view behind paywalls, and review-site grids score satisfaction, not fit for your estate. So here’s TechBag’s synthesis of the AI-security market — tap any vendor to see why it sits where it does.
TechBag Data-Security Grid
Execution strength vs product vision — the classic market map, minus the paywall.
AI-DLP from a data specialist; bi-directional and India-origin.
Platform Breadth × AI Data Control
The grid nobody publishes — data-security platform breadth vs AI data-control depth.
Bi-directional + platform (DSPM/EDRM).
Positions are TechBag’s illustrative synthesis of public review-platform data and vendor documentation — not a reproduction of any analyst graphic. Verify before relying on it.
Seclore AI-DLP vs the AI-security field
Legacy DLP + AI add-ons, AI-security startups, CASB/SSE and Purview AI — honest lanes in a new category; the edge is bi-directional control from a data specialist, plus platform + India origin.
| Dimension | Seclore ARMOR AI-DLP | Legacy DLP + AI add-on | AI-security startups | CASB/SSE AI controls | Microsoft Purview AI | No AI-DLP |
|---|---|---|---|---|---|---|
| Position | AI-DLP from a data-security specialist; bi-directional; India-origin | Traditional DLP adding AI | Dedicated AI-security | SSE adding AI controls | Microsoft-native | The gap |
| AI interaction-layer control | Purpose-built at the AI layer | Bolted-on | Yes — the focus | Via proxy | In Microsoft AI | None |
| Bi-directional (in & out) | Both prompts & responses | Mostly inbound | Varies | Mostly inbound | Within MS | None |
| Copilot over-exposure | Response control + DSPM/EDRM | Not addressed | Some | Not the focus | MS access controls | None |
| Tokenise/mask before model | Bi-directional tokenisation | Redact/block | Varies | Redact | Some | None |
| Broad AI coverage | Public, enterprise, custom AI | Some | Broad | Web AI mainly | Microsoft AI | None |
| Part of a data-security platform | ARMOR (DSPM+EDRM+classification) | DLP suite | Standalone | SSE suite | Purview suite | None |
| India origin & DPDP fit | Mumbai-HQ, DPDP-aware, sovereign | Mostly foreign | Mostly US-origin | Mostly foreign | US-origin | N/A |
| Best fit | AI data control from a data specialist; bi-directional; India-origin | Extending existing DLP to AI | Dedicated AI-security-first | SSE-committed orgs | All-Microsoft AI estates | Nobody — AI leaks data |
Which data security & privacy approach fits you?
Honest fit signals — because the fastest way to lose your trust is to pretend one product wins every scenario.
Choose Seclore AI-DLP if…
- You want AI data control from a data-security specialist
- Bi-directional protection (leakage in + over-exposure out) matters
- You're rolling out Copilot / enterprise AI and worry about over-exposure
- You value an India-origin platform under DPDP
Legacy DLP + AI if…
- You want to extend your existing DLP with basic AI controls
AI-security startups if…
- You want a dedicated, AI-security-first standalone tool
CASB/SSE AI controls if…
- You're SSE-committed and want AI controls in that stack
No AI-DLP if…
- Never — AI adoption leaks sensitive data without it
Seclore ARMOR AI-DLP is one of 21 dlp & insider risk products TechBag carries. The DLP & Insider Risk guide narrows them to a shortlist and shows the reasoning. →
What could this save you?
Drag the sliders (count AI users; IT-hour cost as loaded rate). Estimates assume productivity retained by enabling AI safely rather than banning it, plus reduced incident handling — but the far larger, unpriced win is the avoided breach and DPDP penalty (sensitive data leaking into third-party AI, and Copilot over-exposure, are real and growing). Illustrative.
Loaded cost = salary + overheads per productive hour. Illustrative only — your TechBag quote models your actual environment and modules.
Three ways to consume it
Seclore ARMOR AI-DLP is quote-priced (no public list) — by users, AI scope (public chatbots, copilots, custom AI) and whether you add the wider ARMOR platform (DSPM, EDRM, Classification) for end-to-end AI data security. It's a newer category — confirm current capabilities. TechBag right-sizes it and quotes in INR/GST — Seclore is India-origin.
ARMOR AI-DLP
Best for safe AI adoption
- Control sensitive data to & from AI, in real time
- Bi-directional: leakage in + over-exposure out
- Public chatbots, copilots, custom AI
+ Platform add-ons
Best for a broader rollout
- Scoped to your estate
- Add-on modules as needed
- Phased, right-sized deployment
+ The ARMOR platform
Best for end-to-end AI data security
- Add DSPM (what AI can reach), EDRM (protect), Classification
- Discover, control at AI layer, protect the data
- TechBag scopes the mix
Buy it for less — TechBag pricing beats list
Whatever the list prices above, TechBag negotiates a significantly better deal — with GST-compliant INR invoicing and local support. Ask us for your discounted quote.
Get an India-ready quote
Tell us your requirements and current tools — we’ll model it against what you spend today.
The 8 questions to ask every vendor
Take this into your next vendor call — including ours.
Map how employees use AI — public chatbots, enterprise copilots, custom AI apps — to scope where control is needed.
Identify the sensitive data at risk of leaking into AI (customer data, code, personal data, confidential content).
If deploying Copilot/enterprise AI, consider the over-exposure risk (AI surfacing sensitive data) — needing outbound control.
Confirm the goal is to enable AI safely (not ban it) — controlling data while allowing productivity.
Plan for both inbound (leakage) and outbound (over-exposure) control — not just prompts.
Consider integration with DSPM (what AI can reach) and EDRM (protect the data) for end-to-end AI data security.
Map to DPDP — preventing personal/regulated data leaking into third-party AI, and evidencing control.
Given AI-DLP is emerging, evaluate current capabilities vs your AI usage; size and quote in INR/GST — TechBag scopes it.
Questions buyers ask
Ready to use AI without leaking data?
Scope AI data control (protect sensitive data flowing to and from AI, bi-directionally), enable AI safely instead of banning it, or let a TechBag advisor plan your AI data-security strategy.
Stats, ratings, review counts and pricing are illustrative and sourced from public materials; verify before purchase.