Relogic

AI-Native Studio ยท Research Consulting

Turning Data into
Intelligence

Relogic Solutions is an AI-native innovation studio. We transform unstructured data into intelligent, research-driven outcomes through ethical AI and human-centric design.

Our Services About Us

Organizations we've collaborated with

Google
Microsoft
Amazon
NVIDIA
OpenAI
Meta
Google
Microsoft
Amazon
NVIDIA
OpenAI
Meta
About

Who We Are

Relogic Solutions is an AI-native innovation studio and research consulting hub. We specialize in transforming unstructured data into intelligent, research-driven outcomes.

Our approach is rooted in ethical AI, data analytics, and human-centric innovation. Technology should serve people.

Ethical AI Data Analytics Human-Centric Research Consulting Innovation Studio

Our Focus

  • Clinical data intelligence & bilingual voice recognition
  • Advanced Persistent Threat detection frameworks
  • Unstructured data โ†’ actionable visual stories
  • Ethical AI governance, fairness & explainability
  • Research-driven consulting for enterprises
Projects

Our Solutions

Advanced AI-powered tools for healthcare, cybersecurity, analytics and governance โ€” crafted with precision and ethical intelligence.

Explore All the Services
Analytics Dashboard
Clinical App
Security
ClinTx Engine
Clinical Engine

ClinTx Engine

Clinical data ingestion with bilingual voice recognition and OCR for research-ready medical data.

Voice Recognition OCR HIPAA
APT Detection
Cybersecurity

APT Detection Framework

Unsupervised learning + real-time network anomaly detection for Advanced Persistent Threats.

Unsupervised ML Zero-day
InsightFlow
Analytics

InsightFlow Analytics

Turns raw unstructured data into interactive visual stories and actionable business intelligence.

Visual Storytelling Predictive
EthosAI
Governance

EthosAI Governance

Ethical AI platform ensuring fairness, transparency and accountability from development to deployment.

Fairness Explainability
Our People

ONE TEAM.
DIFFERENT STRENGTHS.

Leadership, advisors and the core team now live together in one dedicated people space. Explore the team, then open any profile to view that personโ€™s individual page.

Meet Our People
01
Leadership

Founders and leadership profiles shaping Relogicโ€™s direction.

View leadership โ†’
02
Advisors

Specialist advisors supporting portfolio, brand and engineering direction.

View advisors โ†’
03
Core Team

Engineering, research, data, legal and product talent building the work.

View core team โ†’
Mobile Experience

Relogic, designed like a real app.

Three product states - onboarding, studio dashboard and AI conversation - rebuilt with device framing, status bars, navigation, app controls and the Relogic logo used throughout.

9:415G  |||  100%
Relogic

Build the future
with intelligence.

Research, AI and digital products shaped around real problems and measurable outcomes.

AINative
R&DResearch
UXHuman
Explore Relogic →
9:415G  |||  100%
RelogicRelogic Studio
+
Your workspace

What do you want
to build today?

RResearch ConsultingEvidence, analysis and study design→ PDigital ProductsStrategy, UX and product engineering→
Active engagementDiscovery Sprint
In progress
9:415G  |||  100%
Relogic
Relogic AI StudioOnline
We have messy clinical survey data. Where should we start?
Start with the research question.

Then we can map variables, data quality, missingness and the analysis plan before building a model.
Can this become a visual research dashboard too?
Yes. We can move from validated analysis into an interactive product once the evidence layer is stable.
Research planData auditDashboard idea
Ask Relogic AI...
↑
Relogic Relogic / Intelligence Map
30 Years of Artificial Intelligence

AI innovation changed industry.
The next wave changes risk.

A visual map of how artificial intelligence evolved from statistical machine learning into deep learning, generative systems and autonomous AI โ€” flowing into finance and manufacturing while exposing persistent adoption gaps, governance challenges and emerging technology risks.

Analysis window 1996 โ†’ 2026

AI evolution & industry impact map

Hover nodes and flows to explore the transformation.

01 AI EVOLUTION 02 INDUSTRY IMPACT 03 VALUE / ADOPTION GAP 04 EMERGING RISK 1996โ€”2005 Statistical ML Rules โ€ข scoring โ€ข optimization 2006โ€”2015 Deep Learning Vision โ€ข prediction โ€ข big data 2016โ€”2026 Generative + Agentic AI LLMs โ€ข multimodal โ€ข agents INDUSTRY Finance Fraud โ€ข risk โ€ข research service โ€ข operations INDUSTRY Manufacturing Vision โ€ข robotics โ€ข planning maintenance โ€ข digital twins GAP 01 Data fragmentation Legacy systems โ€ข silos GAP 02 Pilot โ†’ production ROI โ€ข integration โ€ข reliability GAP 03 Trust & governance Talent โ€ข controls โ€ข adoption RISK 01 Cyber + synthetic fraud Identity โ€ข attacks โ€ข deception RISK 02 Autonomous errors Agents โ€ข actions โ€ข control RISK 03 Systemic dependency Vendors โ€ข models โ€ข infrastructure 1996 SCALE VALUE GAP 2026+
Innovation

AI moved from prediction to action

Enterprise AI has evolved from narrow statistical systems toward generative, multimodal and increasingly autonomous intelligence.

Uncaptured opportunity

Model capability โ‰  business capability

Legacy infrastructure, fragmented data, governance, talent and integration can prevent advanced AI from producing proportional enterprise value.

New risk frontier

Intelligence is becoming operational

As AI systems gain access to tools, workflows and decisions, organizations must manage new cyber, governance, dependency and autonomous-action risks.

Strategic visualization โ€” flow width is illustrative, not a quantitative market measurement.
Start a project ยท Relogic Studio

Tell us what you're building.

Four short sections, about four minutes. We turn every answer into a written assumption, then send back a fixed-scope proposal. We work at the intersection of AI/ML research and production systems across healthcare, finance, logistics and operations โ€” outcomes measured by the people who use them, not just the model.

Project intake 04 steps ยท ~4 minutes
01 / 04 ยท DiscoveryProject brief
Step 01 ยท Discovery

Start with the basics.

Who we're talking to, where to reach you, and the closest fit for the work.

01
Enter your name.
Enter a valid email.

Healthcare

Clinical decision support, triage models and records intelligence.

Finance

Risk models, fraud detection, underwriting and forecasting.

Logistics & supply chain

Demand forecasting, routing and inventory optimisation.

Business operations

Process automation, internal tooling and decision support.

Product development

An AI/ML feature or capability inside an existing product.

Data intelligence

Turn raw operational data into a queryable, trusted asset.

Pick the closest fit.
Step 02 ยท Scope & budget

Make the proposal realistic.

Give us enough context to avoid sending back something generic.

02
Let us know the current stage.
Let us know your timeline.
Pick a range โ€” โ€œnot sure yetโ€ is completely fine.

Email

We'll reply to the work email you entered above.

Phone

A short call to confirm assumptions and scope.

Choose a follow-up method.
Step 03 ยท Project details

Tell us what the form can't guess.

Describe what needs to exist, what isn't working and what matters most.

03
A few sentences is enough to start.
Step 04 ยท Review & send

One final check.

Review the brief. You can jump back to any section before sending it to the studio.

04
Your brief stays between you and the studio.

Sent to the studio.

We read every submission ourselves โ€” no queue, no account manager. Here's what happens next.

01
A written assumptionWe turn your answers into a short brief and confirm we've understood the project.
02
A scoped proposalDeliverables, milestones, price and what's explicitly out of scope โ€” usually within a few days.
03
A phased buildIf you approve the proposal, we start โ€” foundation, core, then launch.