01
Losing customers to slow, frustrating service?
AI assistants that answer on app, WhatsApp and phone day & night and hand complex cases to your team.
Agentic AI, generative AI
Data Engineering & Agentic AI · Asia Pacific and AMER
Trusted data and AI agents that cut losses, speed up service, and keep working after launch.
For mid-size financial services and healthcare companies in Asia Pacific and AMER. We fix the data first, then put AI agents to work on real problems, from a short pilot to production.
Problems we solve
The costly problems we hear from leaders
Start with the issue that is already showing up in your numbers. The technology is how we get there - not the reason to start.
02
Customers are telling you their problems. Is anyone listening?
Analysis of calls, chats and complaints that surfaces issues customers never formally raise.
Generative AI, analytics
03
Selling one product when customers need three?
Models that predict who will leave and what each customer is likely to need next.
Data science, decision science
04
Bad loans and slow collections eating your margins?
Early-warning signals on risky accounts and smarter prioritisation of collections.
Machine learning, decision science
05
Teams buried in documents and manual checks?
Automated reading and checking of KYC, loan and claims documents, with people approving the final step.
Agentic AI, document AI, workflow automation
06
Leaders waiting days for numbers they can trust?
One reliable data platform with dashboards and the ability to ask questions in plain English.
Data engineering, BI, generative AI
Industries we serve
The sectors we work in - and the problems leaders bring us
Five sectors where messy data and manual decisions show up on the P&L. Financial services and healthcare are the centre of the work.
Financial Services
- Customers leave after slow, fragmented service across branch, app and WhatsApp.
- Bad loans and slow collections quietly eat margin.
- KYC, loan and compliance files still move by hand, so work waits on people.
Healthcare & Life Sciences
- Patients and members wait too long for answers on appointments, claims and bills.
- Calls, chats and complaints hold issues that never reach a formal ticket.
- Claims and clinical documents pile up while leaders wait for numbers they can trust.
Insurance
- Claims sit in queues while documents are read by hand.
- Fraud and leakage show up after the payout, not before.
- Underwriting still depends on incomplete files and gut feel.
Retail & E-commerce
- Customers are treated as one segment when their next need is already in the data.
- Demand swings leave shelves empty or stock sitting idle.
- Content and merchandising cannot keep up with the catalogue.
Manufacturing
- Equipment fails before the plant sees it coming.
- Quality varies by line, and root cause takes too long.
- Factory systems and IT still do not share a trusted picture.
How we work
Diagnose, prove it, then keep it running
You do not buy a multi-year transformation up front. You see where AI will pay off, prove it against an agreed goal, then scale what works.
- 1
Diagnose
A short assessment of one business area - where data and AI would save money or grow revenue, and what it would cost to try.
- 2
Pilot
A few weeks, with an agreed business goal. You see a working result before you commit to a larger programme.
- 3
Production and run
We put it into production and stay involved after launch - with the same team accountable for reliability, not a handoff.
The standard we work in
FDE method of deliverables
Forward Deployed Engineering. We sit with the people who do the work and ship inside your environment. A phase is complete when its deliverable exists - a document or a system you can inspect - not when the calendar says so.
- 01Discovery
Discovery summary
The problem as it was stated, the problem we actually found, the constraints, and a success definition that can be tested.
- 02MVP scoping
Scoped plan
The smallest version that proves the outcome on your systems, with a written line around what is out of scope.
- 03Prototype on real data
Working prototype and data-issue log
A prototype that runs on your data, plus each data issue found and how it was handled.
- 04Evaluation
Evaluation report
The pass and fail criteria, and the results against them, before anything is called production.
- 05Production rollout
Live system and response plan
The system running in your environment, with monitoring and a plan for when something breaks.
- 06Feedback loop
Closing summary
What ran, what broke, and what the next use case can reuse on the same foundation.
Why VynelixAI
A small senior team that stays after launch
Large consultancies are built for long programmes and layered delivery. We start with the business problem, prove it in a short pilot, then run what we ship.
We start with the business problem, not the technology
The first question is what is costing you money or growth - slow service, leakage, paperwork, untrusted numbers. The stack comes second.
We prove it in a short pilot before you commit
You see a working result against an agreed goal. Scale is a decision you make with evidence, not a programme you buy on faith.
We stay accountable after go-live
MLOps, LLMOps and AI SRE are part of the engagement - so the system keeps working and improving, with us on the hook.
Our products cut cost and time when they fit
Agent Studio and AI SRE Agent compress delivery. If they do not fit, we still engineer on your stack. Genveth is a dedicated product, not a homepage pitch.
What the buyer cares aboutTypical large consultancyVynelixAI
How quickly you see results
Typical large consultancyProgrammes that run for many months
VynelixAIA working system in weeks, against an agreed business goal
Who works on your project
Typical large consultancyLarge teams, many juniors, people you never meet twice
VynelixAIA small senior team - you know their names
What you get
Typical large consultancySlide decks, then a handoff to another group
VynelixAIA system that runs, plus the people who keep it running
Control and compliance
Typical large consultancyOften an afterthought once the demo is over
VynelixAIBuilt in from day one - audit trails and human approval
Cost of getting started
Typical large consultancyA large minimum commitment
VynelixAIA short, fixed-scope assessment, then a pilot
Evidence
Delivery you can inspect, not invented case studies
We do not publish made-up percentages. Where we have production systems, we say so. Where we are still taking on first clients, we say that too.
10+
Campuses on Genveth
Our talent platform runs in production - 10+ campuses and 5k profiles matched.
Weeks
Typical path to a working pilot
Diagnose, then a short pilot with an agreed business goal - not a long programme first.
Asia Pacific and AMER
Markets we serve
Financial services, healthcare, insurance, retail, and manufacturing. Delivered from Bengaluru.
Limited intake
Founding client programme
We are taking on a small number of first clients in financial services and healthcare. You work directly with our senior team, and we price the first engagement as a partnership.
Ask about founding client accessProducts that accelerate delivery
Use our products when they cut cost and time - not because we need to sell them
Agent Studio and AI SRE Agent are how we compress common work. Genveth, our talent platform, lives on the Products page.
If a product does not fit, we still engineer on your stack. Genveth is available as a dedicated product for universities and hiring teams.
AI Site Reliability Engineering
AI SRE Agent
AI SRE Agent watches your infrastructure and application signals across every major monitoring stack, correlates anomalies into a single root cause, and can safely execute remediation runbooks - before an on-call engineer ever gets paged.
Explore AI SRE AgentAgentic AI Platform
Agent Studio
Agent Studio is a visual, versioned environment for designing, testing, and shipping multi-agent workflows - with native support for MCP tools, RAG retrieval, prompt management, and long-term agent memory.
Explore Agent StudioTechnology
The stack our engineers use - for CTO readers
We stay model-agnostic and cloud-agnostic. Technology supports the business result; it does not lead the conversation.
LLM & Foundation Models
OpenAIAnthropic ClaudeMeta LlamaMistralGoogle Gemini
Agentic & Orchestration
Model Context ProtocolLangGraphAutoGenAgent Studio
Retrieval & Data
Vector DatabasesHybrid SearchElasticsearchApache KafkaApache Flink
Data & Orchestration
Apache AirflowdbtSnowflakeDatabricksBigQueryApache SparkClickHousePrefect
Open table formats
Apache IcebergDelta LakeParquet
Cloud & Platform
AWSS3GlueRedshiftGoogle CloudDataflowPub/SubMicrosoft AzureKubernetesOpenShift
Observability
CloudWatchDatadogGrafanaPrometheusElastic
MLOps & LLMOps
MLflowWeights & BiasesCI/CD PipelinesFeature Stores
From the Blog
Engineering notes from the field
Practical, technical writing from the team building agentic AI, RAG, and AI SRE systems in production.
Agentic AI·Jul 22, 2026
Designing Safe Autonomous Agents: A Practical Governance Framework
Autonomy without governance is a liability. Here's the framework we use to scope, monitor, and audit every agent we ship to production.
Read postRAG & Knowledge Systems·Jun 30, 2026
RAG vs. Fine-Tuning: A Decision Framework for Enterprise Teams
Teams routinely reach for fine-tuning when retrieval would be cheaper, safer, and easier to maintain. Here's how we decide.
Read postAgent Infrastructure·Jun 10, 2026
MCP: The Integration Layer Agentic AI Has Needed All Along
The Model Context Protocol solves the N×M integration problem that's been quietly stalling every agent platform team.
Read postAI News
What's new at VynelixAI
Product launches, milestones, and updates from across our platform.
Product
Oct 22, 2026Agent Studio goes open source in November
In November 2026, VynelixAI will publish Agent Studio as open source so teams can inspect, run, and extend the environment we use to design and ship agents.
Delivery
Oct 16, 2026DataFlow Agent delivered to a retailer in October
In October 2026 we delivered DataFlow Agent to a retailer: a LangGraph agent on Databricks that checks, repairs, and publishes data after a person approves the step.
Product Launch
Jul 30, 2026VynelixAI Launches Agent Studio Marketplace with 200+ Templates
The new marketplace gives platform teams a head start with pre-built, production-tested agent templates and connectors.
Product Update
Jul 5, 2026AI SRE Agent Adds Native OpenShift Support
Platform teams running Red Hat OpenShift can now deploy AI SRE Agent with full topology awareness out of the box.
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Have a data or AI problem that is costing you money? Let’s talk it through.
A 30-minute conversation with a senior person - no slide deck, no invented ROI. Bring the problem that is already on your P&L.