Enterprise knowledge retrieval

Find approved
company knowledge. Verify every answer.

Deepli is an enterprise AI knowledge agent powered by hybrid information retrieval. It searches connected and authorized repositories, ranks evidence, and returns grounded answers with source links across Vietnamese, Japanese, and English.

Request a controlled pilot→ See how it works
Controlled pilots · Scope and capabilities confirmed before deployment
Designed for governed enterprise knowledge retrieval
PDF
Employee Onboarding Policy
/drive · approved repository
DOC
Information Security Training
/drive · approved source
SLK
How do new employees complete security training?
Japanese query · Vietnamese source
→ Grounded answer: Retrieved from approved onboarding material with a source link for verification.
Source-linked evidence
Illustrative flow
500+
Enterprise teams
4.2M
Queries answered
0.3s
Median response
99.9%
Uptime SLA

Connects with every tool your team uses

The enterprise search problem

Your company has information.
It needs reliable retrieval.

The right answer often exists, but documents are fragmented, terminology varies across teams and languages, and access boundaries make enterprise retrieval harder than ordinary web search.

  • Knowledge is fragmented across repositories. Policies, reports, and decisions sit in disconnected systems and file formats.
  • Words differ across teams and languages. A user's terms may not match the terminology or language used in the source document.
  • Useful retrieval must remain governed. Search must stay within the repositories and knowledge boundaries authorized for each user.
47 results · none useful
Q3 APAC revenue target
Q2 2023 APAC summary
APAC offsite agenda
Revenue dashboard — old
Slack: "what's the Q3 target again?"
FY24 deck draft v7 FINAL
Misc · team lunch thread
Fragmented retrieval
Unverified results
A practical starting point
Begin with one difficult knowledge domain.
Request a pilot→ See the retrieval flow
Current product scope

Built for reliable
knowledge retrieval.

Current capabilities are presented by implementation status—not by broad enterprise-AI promises.

01

Hybrid Retrieval

Uses lexical and semantic signals in Elasticsearch to retrieve and rank relevant evidence.

02

Cross-Lingual Retrieval

Supports retrieval across Vietnamese, Japanese, and English at the retrieval layer.

03

Repository-Scoped Access

Restricts search to repositories authorized in Deepli; source-file ACL synchronization is under development.

04

Grounded Answers

Returns answers with links to contributing source documents so users can verify the result.

05

Model Flexibility

Works with OpenAI and selected OpenAI-compatible model endpoints, subject to deployment assessment.

06

Dataset-Specific Tuning

Indexing, retrieval, and interaction behavior can be evaluated and tuned for the customer's data.

Explore capabilities in depth→
How it works

From approved sources
to verifiable answers.

1

Connect

Connect an approved repository and confirm document, security, and access requirements.

2

Index

Extract and normalize supported content, then create search-efficient representations.

3

Retrieve & Answer

Rank evidence, plan the interaction, and answer with source links—or report insufficient evidence.

The Deepli engine

Built for
governed retrieval.

  • 01

    Elasticsearch Retrieval

    Customized analyzers, indices, hybrid queries, and ranking controls support dataset-specific retrieval.

  • 02

    Agentic Interaction

    The agent can answer, refine the search, ask for clarification, or report insufficient evidence.

  • 03

    Authorized Search Scope

    Repository-level controls limit the knowledge space available to each user or role.

Slack
Drive
Notion
Jira
Gmail
CONNECT & NORMALIZE
Approved repository · Text · Metadata
RETRIEVE & RANK
Lexical · Semantic · Access scope
ANSWER WITH SOURCES
Grounded · Verifiable · Multilingual
Loved by teams

Don't take our word
for it.

500+ teams across finance, tech, healthcare, and legal rely on Deepli every day.

We replaced three internal tools with Deepli. Our engineers stopped pinging senior devs in Slack because the answer is just there, cited, in seconds.

HM
Hiroshi Matsuda
VP of Engineering, Leading fintech company

The permission mirroring sold our CISO instantly. No other AI tool respects our ACL graph this cleanly. We went from "absolutely not" to company-wide rollout in 6 weeks.

PR
Priya Ramanathan
CIO, Global financial services firm

RFP responses used to take my team 3 weeks. With Deepli pulling from our past answers, we submit in under 48 hours. Win rate up 18% since rollout.

EC
Emma Choi
Head of Enterprise Sales, Fortune 500 data company
Controlled rollout
Prove retrieval quality before scaling across the company.
Discuss a pilot→ Contact the team
Practical use cases

Start where evidence already creates value.

Deepli supports knowledge retrieval and human decision-making; it does not replace accountable review.

HR & Onboarding

  • Retrieve approved policies
  • Support multilingual onboarding
  • Verify the original source
Explore use case →

Engineering

  • Find runbooks and architecture docs
  • Retrieve past technical decisions
  • Keep incident decisions human-led
Explore use case →

Sales & Compliance

  • Locate approved product knowledge
  • Support human-reviewed drafting
  • Retrieve policies and evidence
Explore use case →
See department use cases→
Straight answers

What Deepli does
and does not claim.

Can Deepli answer every company question?
No. Deepli can answer only when relevant evidence is available in connected, indexed, and authorized knowledge. Otherwise it should clarify or report insufficient evidence.
Does grounding eliminate hallucination?
No system can guarantee zero hallucination. Constrained evidence and source links reduce risk and make verification easier.
Does Deepli mirror every source-file permission?
Not in the current standard release. Search is restricted to repositories authorized in Deepli; source-file ACL synchronization is under development.
Which connector is currently validated?
Google Drive is the currently validated scheduled connector. Additional connectors require staged development, testing, and permission validation.

Bring us one difficult
knowledge domain.

We will test retrieval quality, source grounding, and authorized access—then scale only if the evidence supports it.

Request a controlled pilot→ Contact the team
Deepli capabilities

Search, rank, and answer— with evidence attached.

Deepli combines customized information retrieval with an agentic interaction layer and explicit knowledge boundaries.

Request a controlled pilot→
01 / Context-Aware RAG

Hybrid retrieval finds the strongest evidence.

Elasticsearch combines lexical and semantic signals, metadata filters, and ranking controls. The exact configuration is evaluated against the customer's dataset and representative queries.

  • Customized analyzers and indices
  • Lexical and semantic retrieval
  • Metadata and repository filters
  • Dataset-specific evaluation
Discuss this capability→
What is the approved onboarding security requirement?
PDFEmployee_Onboarding_Policy.pdf
...new employees complete the required information-security training before receiving production access...
XLSXSecurity_Training_Guide.pdf
Japan+$2.4M Singapore+$3.1M Korea+$0.8M
DEEPLI RETRIEVAL RESULT
The strongest evidence indicates that security training is required12. Open the contributing sources before acting.
02 / Neural Knowledge Map

Cross-lingual retrieval at the search layer.

Users can ask in Vietnamese, Japanese, or English and retrieve relevant content written in another supported language—without relying only on surface translation of the final answer.

  • Vietnamese, Japanese, and English
  • Cross-language evidence retrieval
  • Domain terminology can be tuned
  • Quality measured with real queries
Discuss this capability→
Slack Drive Notion Figma Jira Gmail DEEPLI
03 / Zero Hallucination

Grounded answers, open to verification.

The generator receives ranked evidence and returns a concise answer with links to the contributing documents. Grounding reduces risk; it does not guarantee perfect accuracy.

  • Constrained evidence context
  • Links to contributing documents
  • Clarification when intent is unclear
  • Insufficient-evidence response
Discuss this capability→
What is the approved data-retention policy?
The indexed policy states that the applicable period depends on data category and jurisdiction1. Review the governing document2 before making a compliance decision.3.
1
Approved Data Retention PolicyPDF · p.7
2
Regional Compliance GuidanceNOTION
3
Repository source recordCONFLUENCE
04 / Airtight Permissions

Authorized repositories, explicitly scoped.

The current release limits retrieval to repositories authorized in Deepli. Source-file ACL synchronization and real-time permission revocation are roadmap items, not current guarantees.

  • Repository-level access scope
  • Role-aware configuration
  • Source ACL synchronization: roadmap
  • Access-policy evaluation in pilots
Discuss this capability→
Approved_Repository_Scope
/drive · confidential
A
Authorized role
CFO
IN SCOPE
B
Approved pilot user
Finance Lead
IN SCOPE
C
Unassigned role
Marketing
OUT OF SCOPE
Universal connectors

Works with every tool
your team already uses.

Native API-level integrations. No migrations. No duplicated data. Set up in minutes.

Slack
Drive
Notion
Figma
GitHub
Salesforce
Confluence
Jira
Gmail
Dropbox
Linear
Asana

+ 40 more integrations. Custom SDK available for internal systems.

Security & compliance

Enterprise-grade
from day zero.

Deepli is built for regulated industries. Your data stays yours — encrypted, isolated, auditable, and never used to train our models.

SOC
SOC 2 Type II
Certified 2024
ISO
ISO 27001
Info security
HIP
HIPAA
Healthcare ready
GDR
GDPR
EU compliant
Defense in depth
01
AES-256 encryption at rest
02
TLS 1.3 in transit
03
Isolated customer environments
04
Zero model training on your data
05
SSO, SAML, SCIM support
06
Comprehensive audit logs

Evaluate Deepli
on your own knowledge domain.

Use representative queries and expected evidence to measure retrieval, grounding, and access-policy compliance.

Request a pilot→ Contact the team
Practical department use cases

Reliable retrieval
for accountable teams.

Deepli helps people find and verify approved knowledge. Human review remains essential for legal, security, financial, and operational decisions.

Engineering

Find runbooks, design records, and technical context.

Deepli retrieves relevant engineering documents and past decisions. It supports incident investigation but does not claim to automate incident response.

Architecture decision retrieval
Locate relevant RFCs, design documents, and recorded decisions.
Runbook and incident context
Retrieve supporting material while engineers remain responsible for diagnosis and action.
Technical-document search
Search supported specifications, guides, and internal documentation through one interface.
72%
Faster ramp
4hr
MTTR drop
−38%
Interrupts
Engineering Retrieval Flow
1
Engineer asks a question
Service, design, or incident scope
2
Deepli retrieves evidence
Runbooks and technical records
3
Engineer verifies the source
Human-led technical decision
OUTPUT
Relevant technical context with sources
Sales & Support

Reuse approved knowledge in human-reviewed responses.

Deepli can retrieve product, security, and past-response material to support drafting. Customer-facing answers remain subject to responsible review.

Approved-answer retrieval
Find relevant product and security knowledge from approved sources.
Human-reviewed drafting support
Use retrieved evidence to prepare a first draft without treating it as final.
Customer-context lookup
Retrieve indexed account material within the configured repository scope.
85%
Faster RFP
2.4x
Deal velocity
+18%
Win rate
Sales Knowledge Flow
1
Receive a customer question
Product, policy, or security topic
2
Retrieve approved material
Rank relevant prior answers
3
Review and personalize
Human approval before sending
OUTPUT
Evidence-backed draft for review
People Operations

Help employees find approved policies and onboarding material.

Deepli can retrieve role- and repository-scoped HR knowledge with links to the source. Sensitive decisions remain with authorized HR personnel.

Policy retrieval
Find the approved policy and let the employee verify the original document.
Onboarding knowledge
Answer common onboarding questions from connected approved material.
Cross-lingual access
Ask in Vietnamese, Japanese, or English across supported indexed content.
−65%
HR tickets
5 days
Faster onboard
94%
Accuracy
Employee Knowledge Flow
1
Employee asks a question
Policy or onboarding scope
2
Retrieve approved evidence
Within authorized repositories
3
Return answer and source
Escalate sensitive cases to HR
OUTPUT
Verifiable policy guidance
Finance & Operations

Locate financial and operational records for review.

Deepli can retrieve indexed contracts, purchase orders, invoices, and policies. It supports investigation but does not replace financial controls or audit judgment.

Vendor-document lookup
Find relevant contract terms and open the contributing source document.
Policy and record retrieval
Search approved operational records within configured knowledge boundaries.
Review support
Assemble relevant evidence for accountable reconciliation or audit review.
−52%
Close time
$220K
Recovered
100%
Audit trail
Finance Retrieval Flow
1
Analyst identifies a question
Vendor, invoice, or policy scope
2
Retrieve relevant records
Authorized indexed sources
3
Verify and reconcile
Human-controlled decision
OUTPUT
Source-linked records for review
Why Deepli

Built differently
on purpose.

Capability
Deepli
Traditional Search
Generic AI
Inline citations
Permission mirroring
Cross-tool knowledge graph
Never trains on your data
Native JP / EN search
SOC 2 + HIPAA + ISO 27001
"

Deepli cut our legal review cycle from 11 days to under 3 days. For the first time, our contracts team isn't the bottleneck in closing deals.

YT
Yuki Tanaka
General Counsel, Leading e-commerce company
−73%
Review time
8x
Throughput
$1.2M
Savings/yr

Choose one use case
and measure it honestly.

A controlled pilot evaluates retrieval relevance, source correctness, and access-policy compliance before broader rollout.

Discuss a pilot→ Contact the team
Knowledge hub

Resources for
modern leaders.

Stay ahead with the latest in enterprise search, AI ethics, and knowledge management.

Featured Articles

View All→
Insights

The Rise of Contextual AI in 2026

How LLMs are evolving to understand business logic, not just keywords—and what it means for enterprise teams.

📅 Oct 12, 2025✍️ Dr. Kenji Sato
Strategy

Mapping Institutional Memory

A guide to building a neural network of your organization's scattered data, conversations, and decisions.

📅 Sep 28, 2025✍️ Sarah Chen
Security

Security vs. Search: Finding Balance

Implementing permission mirroring without sacrificing search speed—lessons from 500+ enterprise deployments.

📅 Sep 15, 2025✍️ Mark Williams

Upcoming Events

Jan
15

Enterprise Knowledge Summit 2026

A deep dive into AI-driven discovery for modern organizations.

🕐 10:00 AM PST📍 San Francisco / Virtual
Register
Feb
02

Deepli Product Keynote: Winter Release

Unveiling our new multi-modal RAG engine and SaaS connectors.

🕐 2:00 PM JST📍 Virtual Event
Register
Mar
08

Workshop: Building Your Knowledge Graph

Hands-on session with our engineering team on graph architecture.

🕐 11:00 AM JST📍 Tokyo / Virtual
Register
On-demand demo

Ready to see
Deepli in action?

Watch a 15-minute walkthrough of how enterprise teams use Deepli to unlock institutional memory.

Watch On-Demand Webinar
About Deepli

Enterprise retrieval
built for control.

Deepli is a MOR AI product by MOR Software JSC, developed to make approved company knowledge easier to retrieve and verify.

The product direction

Deepli is designed as a product, not a tailoring-only service. The core system provides ingestion, Elasticsearch-based hybrid retrieval, an agentic interaction layer, and source-linked answers.

The standard product is intended to provide a practical starting point. Connector scope, access requirements, deployment model, and retrieval quality are confirmed during a controlled pilot.

Custom integration, local-model deployment, and dataset-specific tuning are optional implementation services around the core product—not substitutes for a strong product foundation.

About MOR AI

MOR AI develops AI products and implementation capabilities within MOR Software JSC.

For Deepli, the current focus is governed enterprise knowledge retrieval across supported repositories, languages, and deployment environments.

Future product development may include additional connectors, deeper source-level authorization synchronization, richer document understanding, and domain-specific optimization.

Parent company
MOR Software JSC
Top 10 Vietnam ICT · Est. 2016
550+
Engineers
1,000+
Projects
550+
Global clients
5x
Sao Khue Award
ISO 9001:2015ISO 27001:2013VINASA Top 10
Global offices
🇻🇳Ho Chi Minh City · Hanoi · Da Nang
🇯🇵Tokyo · Osaka · Nagoya
🇰🇷Seoul
🇬🇧Cambridge
Product principles

Three principles behind Deepli.

01

Evidence before confidence.

Answers should be grounded in retrieved evidence and linked back to contributing documents for verification.

02

Authorization defines the search space.

Useful enterprise retrieval must remain within explicitly approved repositories and access boundaries.

03

Quality must be measured locally.

Retrieval quality depends on the dataset, terminology, query distribution, and judgments—so pilots use real questions and evidence.

Evaluate Deepli with your own knowledge.

Start with a controlled scope and measurable quality criteria.

Request a Deepli pilot→ Explore MOR Software
Pilot scope and pricing

Priced around actual
deployment requirements.

Deepli pricing depends on the knowledge scope, integration and access requirements, deployment model, and evaluation work required for the customer environment.

Why pricing starts with scope
A responsible estimate requires the indexed corpus, connector requirements, access model, deployment environment, model choice, and quality targets. Those factors are confirmed before a written proposal.
Team
Small teams getting serious about knowledge.
20–100 seats · cloud-hosted · up to 5 connectors
Starts at Let's talk
Everything you need to start
  • Context-aware RAG search
  • Up to 5 native connectors
  • Permission mirroring
  • Bilingual EN / JP
  • Email support, 8/5
Get a quote→
Most common
Business
Mid-market teams rolling out across departments.
100–1,000 seats · cloud or VPC · unlimited connectors
Custom quote Scoped to your usage
Team plan, plus
  • SSO (SAML, OIDC), SCIM provisioning
  • Unlimited connectors + custom SDK
  • Audit logs & admin dashboard
  • Dedicated Customer Success Manager
  • 99.9% uptime SLA · 24/5 support
Get a quote→
Enterprise
Regulated industries, global rollouts.
1,000+ seats · on-prem / air-gapped options · custom LLM
Let's scope Annual contract
Business plan, plus
  • On-prem, VPC, or air-gapped deployment
  • Bring-your-own LLM (Azure, Bedrock, self-host)
  • Dedicated solutions architect
  • Custom DPA, MSA, regulatory review
  • 99.99% SLA · 24/7 support · on-call engineer
Talk to sales→
Scoping inputs

Three factors shape the implementation.

The objective is a transparent scope tied to real technical requirements and measurable outcomes.

01
Knowledge scope
The repositories, document volume, formats, update frequency, and languages included in the pilot or deployment.
Confirm
Corpus · formats · languages
02
Integration & access
Connector maturity, synchronization requirements, repository boundaries, roles, and source-permission complexity.
Confirm
Connector · roles · policies
03
Deployment & models
Cloud, restricted network, or on-premises requirements; OpenAI or selected compatible endpoints; and operational constraints.
Assess
Cloud · local · on-prem
Controlled pilot scope

What a pilot is designed to establish.

The exact deliverables are agreed in writing for the selected repository and knowledge domain.

Defined repository and use-case scope
Connector and document-format assessment
Configured repository-level access boundaries
Representative query and evidence set
Indexing and retrieval configuration
Vietnamese, Japanese, and English evaluation where applicable
Source-grounded answer evaluation
Pilot findings and rollout decision criteria
Pilot process

From discovery to measured decision.

Timing depends on source readiness, security review, integration complexity, and evaluation-set preparation.

01STEP
Discovery and scope
Confirm the knowledge domain, repository, user group, access constraints, and target questions.
02STEP
Technical assessment
Review connectors, document formats, infrastructure, model endpoints, and security requirements.
03STEP
Configure and evaluate
Index the agreed corpus, tune retrieval, and test representative queries against expected evidence.
04STEP
Measure and decide
Review relevance, source correctness, answer acceptance, access compliance, and the requirements for expansion.

Enterprise AI pricing is broken.
We're trying to fix it.

Most of our competitors hide everything until you've sat through three sales calls. Others bury you in credit math that nobody — not even their own reps — can explain. We think there's a better way.

Get your quote→
TypicalOpaque pricing, 6-month procurement, $70K paid POC before you see the product with your data.
TypicalCredit-based billing. Your finance team can't forecast spend. Admins disable AI features to stay in budget.
DeepliTransparent drivers, 14-day timeline to pilot, free discovery call, written quote in 48 hours.
DeepliFixed seat pricing + optional usage overages. Predictable budgets. No AI-access gatekeeping.
Pilot FAQ

What to expect before a proposal.

Is Deepli sold as a fixed self-service package?
The core product is standardized, but enterprise deployment scope varies by connector, corpus, authorization model, infrastructure, and quality requirements.
Can we begin with one team or repository?
Yes. A controlled pilot should start with a bounded, high-value knowledge domain and expand only after agreed quality and governance thresholds are met.
What is measured in the pilot?
Typical measures include retrieval relevance, source correctness, answer acceptance, access-policy compliance, and time to a verified answer.
Are local models or on-premises deployment available?
Selected OpenAI-compatible local endpoints are supported. On-premises or restricted-network deployment requires a technical assessment.
Which connector is validated today?
Google Drive is the currently validated scheduled connector. Additional connectors require staged development and permission testing.

Define a measurable pilot scope.

Share the repository, knowledge domain, user group, and representative questions. We will confirm technical feasibility before proposing the engagement.

Discuss pilot scope→ Book a live demo
Let's talk

We're here to help.

Whether you want a live demo, a security review with your CISO, or just to chat about use cases — our team responds within 4 business hours.

Get in touch

Tell us a bit about your team. We'll match you with the right specialist — solutions architect, security engineer, or executive sponsor.

By submitting, you agree to our privacy policy. We'll never share your info.

We reply within 3 working days.
Email us directly
Demo & Support contact@deepli.io
Our offices
🇻🇳
Ho Chi Minh City (HQ)
Mekong Tower 10F, 235-241 Cong Hoa
Ward 13, Tan Binh, HCM
🇻🇳
Hanoi
B1 Roman Plaza Building 25F, Hanoi
🇻🇳
Da Nang
VDB Building 12F, 74 Quang Trung, Da Nang
🇯🇵
Tokyo
Unity Ikebukuro Building 4F
2-35-4 Minami Ikebukuro, Toshima-ku
🇯🇵
Osaka
TK Building 2F, 3-15-5 Toyosaki, Kita-ku
🇯🇵
Nagoya
Meikou Building 2F, 1-17-13 Nishiki
Naka-ku, Nagoya, Aichi 460-0003
🇰🇷
Seoul
Magok Grand Twin Tower Block A
799-7 Magok-Dong, Gangseo-gu
🇺🇸
Cambridge, MA
CIC Cambridge Innovation Center
One Broadway, Cambridge MA 02142
Before you reach out

Common questions, instant answers.

How long is the free trial?
14 days, full feature access, no credit card required. Most teams see value by day 3.
Do you offer on-premise deployment?
Yes — for qualifying Enterprise customers in regulated industries. Deployment inside your VPC or on-prem is available on our Platinum plan.
Can we pilot before rolling out to the whole company?
Absolutely. We typically pilot with a 20–50 person team for 4–6 weeks before broader rollout. We'll help you design the pilot and measure impact.
What's your pricing model?
Per-seat with volume discounts, plus a platform fee for Enterprise features (SSO, dedicated infra, custom connectors). Contact sales for exact quotes — we'll tailor to your usage profile.