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Relevance Lab

Relevance Lab is a next-gen technology services partner, born in the cloud and re-imagined for GenAI.

We guide enterprises through strategic AI adoption, leveraging deep cloud expertise to build frictionless, intelligent businesses driving real outcomes. CIGNEX is a global consulting company offering solutions, services, and platforms on Open Source, Cloud, and Automation technologies. Since 2000, CIGNEX has been delivering enterprise-class solutions, which are built using leading platforms & can easily be integrated with existing systems to achieve unparalleled results. By leveraging multiple delivery models, we help organizations around the world to increase revenue, achieve business goals, gain competitive advantage and maximize customer satisfaction while significantly reducing the cost of doing business. With our client-focused consultative approach, we have delivered over 900 enterprise solutions globally to clients across various industries to meet their business and technical requirements. We offer various project engagement models – Onsite/Onshore, Offshore, Hybrid (Onsite + Offshore), and EDC (Extended Development Center). EDC offers an enhanced level of engagement facilitating a strategic partnership with the clients by setting up a center that leverages our processes, infrastructure, and operational capabilities. CIGNEX’s process infrastructure covers the quality management system (assessed and appraised at CMMi ® Ver 1.3 Level 3), ISO 20000:2011 certified based on ITIL framework and information security management system (ISO 27001:2013 certified). PARTNERSHIPS
We partner with leading technologies & platforms and leverage them to address business challenges for enterprises across industries. Open Source: Liferay | Alfresco | MongoDB | Elastic Search | Red Hat | Confluent (Kafka) | Acquia
Cloud: AWS | GCP | Salesforce | ServiceNow
Automation: UiPath | Automation Anywhere | Celonis | Appian (Low Code)

09/08/2026

𝗕𝗶𝗴 𝗻𝗲𝘄𝘀 𝗳𝗿𝗼𝗺 𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 𝗟𝗮𝗯!
We are pleased to announce a 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗺𝗮𝗷𝗼𝗿𝗶𝘁𝘆 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗶𝗻 𝗸𝗮𝗺𝗮𝗻.𝗮𝗶, an enterprise AI platform specializing in autonomous AI agent systems and intelligent workflow automation.

𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜 𝗶𝘀 𝗲𝗻𝘁𝗲𝗿𝗶𝗻𝗴 𝗮 𝗻𝗲𝘄 𝗽𝗵𝗮𝘀𝗲. Organizations are moving beyond pilots and proofs of concept. They need trusted partners who can securely integrate AI into real business processes, connect it with the systems and data that run the business, and deliver measurable outcomes at scale.

This investment brings together:
𝗥𝗲𝗹𝗲𝘃𝗮𝗻𝗰𝗲 𝗟𝗮𝗯: more than a decade of AI engineering, cloud, data, automation, and enterprise delivery expertise
𝗸𝗮𝗺𝗮𝗻.𝗮𝗶: an AI platform built to help enterprises deploy secure, intelligent agent ecosystems

Together, we’re helping enterprises operationalize AI securely—turning experimentation into production-ready outcomes.

We are excited about what this next chapter means for our customers, our teams, and the future of Enterprise AI.
𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗮𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗺𝗲𝗻𝘁: https://www.relevancelab.com/newsroom/relevance-lab-accelerates-ai-enterprise-transformation-with-strategic-majority-investment-in-kaman-ai

07/01/2026

It's the final day of 𝗔𝗪𝗦 𝗣𝘂𝗯𝗹𝗶𝗰 𝗦𝗲𝗰𝘁𝗼𝗿 𝗦𝘂𝗺𝗺𝗶𝘁, 𝗪𝗮𝘀𝗵𝗶𝗻𝗴𝘁𝗼𝗻 𝗗𝗖.
We're here showcasing 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 — one of the top two partner solutions globally recommended by 𝗔𝗪𝗦 𝗳𝗼𝗿 𝗛𝗶𝗴𝗵𝗲𝗿 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗰𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 — along with our solutions for Healthcare and Government.

Let's talk about:
🔹 Secure, governed, and scalable research environments on AWS
🔹 Research cost governance with our FinOps Portal
🔹 How institutions are accelerating research and innovation with Research Gateway
🔹 AWS Marketplace procurement and customer success stories

If you're attending today, we'd love to connect before the event wraps up.

Explore Research Gateway: https://www.relevancelab.com/platforms/research-gateway

06/16/2026

Some evenings stay with you long after they're over. 🍽️
Our team recently visited Ashirwad Sevashrama in Bengaluru—a home that has been quietly doing the important work of caring for children with warmth, dedication, and compassion.

What began as an evening of sharing a meal turned into an opportunity to connect, listen, and spend quality time together. There was laughter, conversation, and a genuine sense of togetherness that stayed with us long after the evening ended.

For us, CSR is about showing up for communities in meaningful ways. Not through grand gestures, but through small moments of connection that remind us of the value of kindness, empathy, and being present.
We're grateful to Ashirwad Sevashrama for welcoming us so warmly and for allowing us to be part of such a special evening. 💙

05/22/2026

The next enterprise advantage won’t be automation.
It will be autonomy.

For the last decade, enterprises focused on becoming *software-defined*:
☁️ Cloud-first architectures
⚙️ DevOps and automation
📈 Elastic scalability
🚀 Faster digital delivery

That shift transformed infrastructure into innovation engines.

Now we’re entering the next paradigm:

👉 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀.

This is bigger than adding copilots or chatbots. It’s about systems that can:
• Reason instead of just execute
• Predict instead of react
• Continuously optimize instead of follow static workflows

We’re moving from 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 → 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝘆.

Here’s what that looks like in practice:

🔹 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗽𝗲𝗿𝗰𝗲𝗽𝘁𝗶𝘃𝗲
AI-driven cloud governance, self-healing systems, and GenAI-generated IaC are reducing migration effort and improving compliance in real time.

🔹 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲-𝗳𝗶𝗿𝘀𝘁
AI-augmented DevOps now enables:
• Automated testing
• Intelligent code reviews
• Faster modernization of legacy systems
• 30–70% productivity gains

🔹 𝗗𝗮𝘁𝗮 𝗲𝘃𝗼𝗹𝘃𝗲𝘀 𝗶𝗻𝘁𝗼 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗳𝗮𝗯𝗿𝗶𝗰𝘀
AI-powered data mapping and natural-language analytics are transforming data from static pipelines into contextual business intelligence.

🔹 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 𝗯𝗲𝗰𝗼𝗺𝗲 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀
AIOps and AI service desks are now:
• Predicting incidents
• Auto-remediating issues
• Resolving up to 70% of L1 tickets autonomously

The pattern is clear:
The future enterprise stack will combine:

✅ AI-Augmented Engineering
✅ Intelligent Infrastructure
✅ Connected Data & Insights
✅ Autonomous Operations

At Relevance Lab, we’re seeing forward-thinking enterprises move beyond AI experimentation and toward production-grade AI systems that create measurable business outcomes.

The biggest shift isn’t technological.
It’s operational.

The enterprises that win won’t just be digital-first.
They’ll be intelligent by design.

Read our full breakdown on how we are architecturalizing this shift for enterprises: https://www.relevancelab.com/post/from-software-defined-to-ai-powered

05/21/2026

Most enterprises want to adopt Generative AI.
But for organizations operating inside Trusted Research Environments (TREs) — healthcare, higher education, life sciences, and government research — the challenge isn’t innovation.

It’s governance.

Sending sensitive research data to public LLMs creates immediate concerns around:
🔒 Data residency
🔒 Compliance
🔒 Auditability
🔒 Shadow AI usage
🔒 Access control

That’s why the concept of “LLM in a Box” is gaining momentum. Instead of moving data to AI, organizations are bringing AI to the data.

The model is compelling because it enables:
✅ Private GenAI deployment inside secure environments
✅ GPU-enabled infrastructure for training and inference
✅ Internal chat, copilots, and RAG systems without exposing sensitive data externally
✅ Fine-tuning on governed datasets
✅ Enterprise governance controls integrated from day one

The bigger shift:
Enterprise AI adoption is moving from experimentation → operationalization.

And operational AI requires:
➡️ secure-by-design architectures
➡️ governed AI workflows
➡️ domain-specific copilots
➡️ trusted internal AI platforms

One example stood out:
A health sciences institution deployed a private GenAI environment inside their TRE and enabled researchers to:
• summarize research material
• generate starter Python/R workflows
• securely search internal knowledge
• fine-tune domain models internally
—all while maintaining compliance and reducing shadow IT risk.

The real value isn’t just security.
It’s enabling researchers and analysts to use GenAI safely inside workflows they already trust.

Organizations that solve secure AI infrastructure early will be in a much stronger position to scale AI adoption later.
Read the full article here: https://www.relevancelab.com/post/llm-in-a-box-trusted-research-environment-secure-genai

04/30/2026

We’re in Boston.
Today, Relevance Lab is co-sponsoring 𝗜𝗻𝗻𝗼𝘃𝗶𝘀𝗶𝗼𝗻 ’𝟮𝟲 with Findability Sciences and IBM Research at the IBM Watson Research Center.

A room full of enterprise leaders having honest conversations about what it actually takes to run AI at scale:
– Moving beyond pilots to measurable outcomes
– Learning from leaders who’ve operationalized AI
– Taking back frameworks you can apply immediately

Closing the evening with the Global AI Awards and a private Charles River cruise — framed by Harvard University and Massachusetts Institute of Technology.

Follow along for updates.

04/15/2026

We're co-sponsoring 𝗜𝗻𝗻𝗼𝘃𝗶𝘀𝗶𝗼𝗻 '𝟮𝟲 in 𝗕𝗼𝘀𝘁𝗼𝗻 on 𝗔𝗽𝗿𝗶𝗹 𝟯𝟬.
It's an invite-only 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜 𝗦𝘂𝗺𝗺𝗶𝘁 hosted by Findability Sciences at IBM Watson Research Center.

Here's what's on the agenda:
• Talks from leaders who are actually running AI at scale
• Real business cases, not theory
• Workshops you can use the week after
• An exclusive field visit to the MIT Museum Exhibition: "AI: Mind the Gap"
• A special track on AI in agriculture
• The Global AI Awards
• An evening on the Charles River

If you're working on AI in your organisation and want to be in the room, link in comments.

03/27/2026

GenAI in Pharma and Life Sciences has moved beyond experimentation.
The real question now: 𝘄𝗵𝗼 𝗰𝗮𝗻 𝘀𝗰𝗮𝗹𝗲 𝗶𝘁—𝘀𝗲𝗰𝘂𝗿𝗲𝗹𝘆 𝗮𝗻𝗱 𝗲𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲𝗹𝘆?

Across the industry, the mandate is shifting.
GenAI is no longer a tactical add-on—it’s becoming the engine behind R&D acceleration, clinical outcomes, and operational excellence.

The shift is clear:
🔹 From isolated pilots → Unified platforms
🔹 From discrete use cases → Enterprise-wide impact

But this is where most organizations stall.
Escaping the “pilot trap” requires more than models. It demands governance, data readiness, and AI-native architecture.

At Relevance Lab, we help pharma leaders move from AI-curious to AI-native—scaling securely, compliantly, and with real enterprise impact.

Explore the trends shaping what comes next: https://www.relevancelab.com/post/ai-for-healthcare-genai-agents-pharma

03/24/2026

A day rooted in giving, connection, and joy!

As part of our CSR initiative, our team recently visited the Blind People’s Association in Ahmedabad, an organization doing incredible work to empower persons with disabilities through education, skill development, rehabilitation, and healthcare support.

Spending time with the children reminded us that impact goes beyond intent. It lives in shared moments. From distributing essential items to playing games and simply being present, every interaction reflected the true spirit of togetherness.

The work being done here in inclusive education, assistive technology training, and community-based rehabilitation continues to enable individuals to lead independent and confident lives.

We’re grateful for the experience and inspired to keep contributing in ways that are meaningful, human, and lasting.

03/24/2026

𝗖𝗹𝗼𝘂𝗱 𝘂𝗻𝗹𝗼𝗰𝗸𝗲𝗱 𝘀𝗰𝗮𝗹𝗲 𝗳𝗼𝗿 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵.
𝗖𝗼𝘀𝘁 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗱𝗶𝗱𝗻’𝘁 𝗸𝗲𝗲𝗽 𝘂𝗽. 📉

For many research institutions, AWS enabled modern scientific computing at scale. But one massive challenge remains: 𝗠𝗮𝗻𝗮𝗴𝗶𝗻𝗴 𝗮𝗻𝗱 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝗰𝗹𝗼𝘂𝗱 𝗰𝗼𝘀𝘁𝘀.

Research IT, P*s, and finance teams are still asking:
🔹 Which project is consuming the budget?
🔹 Are costs mapped to the right Cost Centre?
🔹 Which Slurm jobs drove this month’s GPU spend?

The problem isn’t effort — it’s fit.
Most FinOps tools are built for enterprise IT, not for 𝗴𝗿𝗮𝗻𝘁-𝗳𝘂𝗻𝗱𝗲𝗱, 𝗺𝘂𝗹𝘁𝗶-𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀.
The result? Manual spreadsheets. Tagging gaps. Billing surprises.

We partnered with AWS and research institutions to build a better approach.
Announcing 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗙𝗶𝗻𝗢𝗽𝘀 — a purpose-built solution designed for research environments.

It brings everything together:
✅ Project-based visibility (Cost Centre → Project → User)
✅ HPC & Slurm cost attribution
✅ Phantom asset detection (identify hidden costs)
✅ Automated, finance-ready chargebacks

👉 Read more about this approach to research cloud cost management→ https://www.relevancelab.com/post/introducing-research-finops

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