What if our internal docs are messy and unstructured?

That's normal. We handle document parsing, OCR for scanned files, metadata extraction, and intelligent chunking. Messy data is the default — we're built for it.

How do you handle access permissions?

The assistant integrates with your identity provider (Okta, Azure AD, Google Workspace). When a user asks a question, the retrieval layer only searches documents that user has permission to access.

Can the assistant generate reports, not just answer questions?

Yes. Assistants can draft reports, create summaries, generate presentation outlines, and produce formatted outputs based on retrieved data. They're content generators, not just search engines.

What LLMs do you use under the hood?

Depends on the use case. We evaluate GPT-4o, Claude, Mistral, and Llama for each deployment based on accuracy, speed, and cost. For sensitive environments, we deploy open-source models in your private cloud.

How do you measure if the assistant is actually helping?

We instrument everything: queries per user, time-to-answer, accuracy ratings, content generated, and self-reported time savings. Monthly reports show ROI trends so you can justify continued investment to leadership.

AI Assistants

Give Every Employee a
Personal AI Assistant

We build AI assistants that sit inside your team's daily tools — answering questions from internal docs, drafting reports, summarizing meetings, and surfacing insights from data. Think copilot for your entire workforce, trained on your company's knowledge.

Build Your AI Assistant Explore Solution

93%

Document Search Speed

86%

Draft Quality Score

78%

User Adoption Rate

89%

Knowledge Accuracy

3.2hrs Saved Per Employee Per Week

89% Query Accuracy on Internal Docs

25+ Assistants Deployed

Use Cases

AI Assistants Across the Organization

Every department has knowledge bottlenecks. AI assistants break them open.

📊

Financial Analyst Assistant

Pulls data from multiple reporting systems, generates charts, drafts quarterly summaries, and answers questions about historical performance — saving analysts 5+ hours weekly.

Finance

⚖️

Legal Research Assistant

Searches through contracts, regulations, and case law to surface relevant precedents. Drafts clause comparisons and flags potential risks in new agreements.

Legal

👥

HR Policy Navigator

Employees ask questions about leave policies, benefits, and procedures in natural language. The assistant finds the right policy, summarizes it, and links to the full document.

Human Resources

🔬

R&D Knowledge Assistant

Engineers search internal research papers, experiment logs, and design docs using natural language. Surfaces related prior work to prevent duplicate efforts.

Engineering

💰

Loan Officer Assistant

Pulls applicant data, checks against lending criteria, drafts preliminary assessments, and flags missing documentation — cutting loan processing time by 40%.

Lending & FinTech

Core Capabilities

Core Capabilities of Our AI Assistants

More than search — assistants that understand context, generate content, and learn from usage.

🔍

Semantic Enterprise Search

Natural language search across documents, wikis, emails, and databases. No more keyword guessing — ask questions and get direct answers with citations.

✍️

Content Generation & Drafting

Draft emails, reports, proposals, and summaries in your company's tone. Assistants learn from your existing documents to match style and terminology.

📊

Data Analysis & Visualization

Connect to spreadsheets, databases, and BI tools. Ask questions in plain English and get charts, tables, and insights without writing SQL.

🗂️

Meeting Intelligence

Transcribe meetings, extract action items, generate summaries, and distribute notes to attendees — integrated with Google Meet, Zoom, and Teams.

🔐

Role-Based Knowledge Access

Assistants respect your permission model. Finance teams see financial data, HR sees HR policies — no accidental cross-department data exposure.

📱

Multi-Platform Availability

Available in Slack, Teams, browser extension, mobile app, or embedded in your internal tools — wherever your team works.

How It Works

How We Build Your AI Assistant

📚

Knowledge Source Mapping

We catalog every internal knowledge source — wikis, drives, databases, CRM, ticketing systems — and assess data quality and access patterns.

🏗️

Assistant Architecture

We design the retrieval pipeline, content generation capabilities, and integration points based on your team's most frequent needs.

🔗

System Integration

The assistant gets connected to your tools — Google Workspace, Microsoft 365, Slack, Confluence, Salesforce, or custom internal systems.

🧪

User Acceptance Testing

A pilot group of 10-20 users tests the assistant for two weeks with real work tasks. We measure accuracy, usefulness, and adoption friction.

📈

Company-Wide Rollout

Phased rollout with training sessions, usage dashboards, and a feedback loop that feeds into weekly optimization cycles.

Your Team's Knowledge Shouldn't Be Trapped in Documents.

Let us build an AI assistant that makes your institutional knowledge instantly accessible to everyone.

Book Free Consultation

🧑‍💼 Workforce Multiplier

Every employee works faster with an AI assistant at their side.

AI assistants don't replace your team — they eliminate the time wasted searching for information, formatting reports, and answering the same questions colleagues ask every week.

3.2hrs

Saved Weekly Per Person

89%

Query Accuracy

78%

Adoption in 30 Days

4.5x

ROI in Year One

Key Benefits

Enterprise-Ready from Day One

AI assistants touching internal data need to be secure, permissioned, and compliant. We don't treat these as afterthoughts.

✓

Permission-Aware Retrieval

The assistant only surfaces information the user is authorized to see. Integrates with your existing IAM and directory services.

✓

Data Residency & Compliance

Deployable in your cloud, your region, your VPC. No data leaves your approved infrastructure. Compliant with SOC 2, GDPR, and HIPAA where needed.

✓

Usage Analytics & ROI Tracking

Dashboards showing queries per department, time saved, accuracy trends, and adoption rates — so you can prove ROI to leadership.

Why OpenMalo

Why Teams Choose Us for AI Assistants

We build assistants people actually use — not shiny demos that get abandoned in a month.

🎯

Adoption-First Design

We obsess over user experience. If the assistant isn't faster than the current way of doing things, people won't use it. We benchmark against existing workflows.

🏦

Regulated Industry Experience

Built assistants for financial services, healthcare, and legal teams where data access, accuracy, and audit trails are table stakes.

🔗

Deep Integration Expertise

We don't just connect to APIs — we understand data models inside Salesforce, SAP, and legacy systems so the assistant retrieves the right data, not just any data.

📊

Measurable Productivity Gains

Every deployment includes before/after measurement. We track time saved, queries answered, and content generated to prove ROI within 90 days.

🛡️

Zero Data Leakage Architecture

Your documents and queries never train third-party models. We use retrieval-only architectures and private LLM deployments when required.

⚡

Fast Time to Value

Pilot in 3 weeks, company-wide in 8. We've refined the playbook across 25+ deployments so nothing is built from scratch.

Get Started

What Would Your Team's AI Assistant Do?

Describe the knowledge bottlenecks your team faces — we'll design an assistant blueprint and share it within 24 hours.

Free knowledge source assessment

Custom assistant architecture proposal

Pilot program for up to 20 users

Response within 24 business hours

No vendor lock-in

Featured Case Study

Case Study

Financial Services

Asset Management Firm Saves 840 Analyst Hours Annually with AI Research Assistant

A 200-person asset management firm had analysts spending 30% of their time searching for data across Bloomberg terminals, internal research memos, and regulatory filings instead of doing actual analysis.

840hrs

Annual Time Saved

89%

Query Accuracy

3wk

Time to First Pilot

The Challenge

The Problem

Institutional knowledge was scattered across dozens of systems, making simple research tasks unnecessarily time-consuming.

Analysts averaged 47 minutes searching for a single data point across Bloomberg, internal drives, and compliance databases

New hires took 4-6 months to learn where information lived and how to access it efficiently

Duplicate research was common — teams unknowingly repeated work done by colleagues in other offices

Quarterly report drafting consumed 3 full days per analyst because data had to be manually gathered from 8+ sources

Our Approach: We built an AI assistant connected to the firm's internal research repository, regulatory filing database, market data feeds, and CRM. Analysts ask questions in natural language and get direct answers with source citations. The assistant also drafts report sections, generates charts from data queries, and flags relevant recent research from other teams. Deployed in Slack and as a browser extension.

FAQ

Frequently Asked Questions

Conceptually yes, but practically very different. Our assistants are grounded in your specific data, respect your permission model, and run in your infrastructure. They don't hallucinate from internet training data — they retrieve from your actual documents and databases.