Large Language Models
Frontier LLMs on Vertex AI and Azure; the right model per task, swappable.
Agentic AI for assessments, documents and workflows.
See how Splashgain combines vision, document processing and AI agents to power Eklavvya, DocuExprt and ePravesh, with integrations into your existing systems.
Apply agentic AI to the systems your team already uses
Explore custom AI agents for sales follow-ups, invoice reconciliation, customer support and reporting. Start with one process, define the approvals and connect the records it needs.
Explore AI agent development servicesFour layers, not four buzzwords
Each layer contains the one inside it. The four words get swapped around in vendor decks — they are not the same thing, and the gap between the second and the fourth is what you are actually buying.
Agentic AI
Where we buildRuns the whole job. Several agents, one goal, guardrails, and a way back.
AI Agents
Acts on the answer. It has tools, memory, and permission to use them.
Gen AI
Where most AI projects stopProduces an answer. Ask it, and it writes, scores or summarises.
AI & ML
Learns patterns from data. It classifies, predicts and reads.
The same difference, in four questions
Gen AI
What you get
Text you then act on
What it remembers
The conversation
When it is wrong
You catch it
When it runs
When someone asks
Agentic AI
What you get
A task already finished
What it remembers
Your system of record
When it is wrong
It rolls back and pages a human
When it runs
On a schedule, unattended
Four capabilities, one engine
Every product draws on the same models. What we learn proctoring an exam improves how we read a marksheet.
Vision AI
Computer vision that verifies candidate identity, watches for exam-hall malpractice and reads handwritten answer sheets.
Eklavvya
Trained on
Live proctoring sessions and scanned answer scripts from Eklavvya exam deployments — not stock footage.
Outputs
- Real-time face detection and identity verification
- Object and behavior flagging — phones, tab-switching, unauthorized apps
- Handwriting OCR that converts answer scripts to searchable digital text
Document AI
Extraction and verification models that read and validate government IDs and academic documents.
DocuExprt
Trained on
Government-issued IDs, marksheets, certificates and admission documents processed through DocuExprt.
Outputs
- OCR and field extraction from PDFs, images and scans
- Government database checks — Aadhaar, PAN, DigiLocker
- Tamper and signature detection across 20+ document types
Generative Evaluation
Models that assess free-form work and generate the instruments used to test it.
Eklavvya
Trained on
Manually evaluated answer sheets — evaluators grade the first 20–25% of a batch, and the model learns the marking pattern before grading the rest.
Outputs
- Descriptive answer scoring with explained feedback
- Question paper generation from a syllabus, tagged to Bloom’s Taxonomy
- AI-conducted video and telephonic interviews, and adaptive case-study assessments
Agentic Workflows
The layer that connects the platform to the systems an institution already runs — as an API, a no-code automation, or an AI agent.
Eklavvya and DocuExprt
Trained on
Built on documented REST endpoints, webhooks and Model Context Protocol servers shared across all three products.
Outputs
- Documented API endpoints with webhooks for real-time status
- n8n and Make workflow connectors
- Model Context Protocol servers so AI assistants can query the platform directly
LLMs, orchestration and automation — how the agents actually run
AI Orchestration
n8n, MCP servers and REST APIs chain retrieval, checks and notifications.
Process Automation
Ingestion, results and follow-ups run on schedule; people review exceptions.
Applied AI Technology
Vision, OCR and evaluation models trained on our own production data.
Four disciplines behind every agent we ship
Ask agentic software the same question twice and you can get two answers. These four disciplines are what our engineers are held to.
Measuring what the model does
Every agent ships against a scored eval set drawn from real data.
Fundamentals before the model
Cost, latency, failure modes and access rules first, so models can be swapped.
Building with agents, under review
Our engineers use coding agents daily; a named person owns every merge.
Shaping the build with you
We shape the spec with your team and test a narrow version early.
Underneath all four is an assumption that this field keeps moving. What we ship next year will not be built the way this was.
The same reporting layer, whichever product produced the data
Scores, competencies and throughput come out of one analytics engine, so an exam result, a verified document and an admission round are all measured the same way and can be read side by side.
- Competency and topic-level breakdowns
- Cohort, centre and round comparisons
- Exports and API access to every figure
Ready to see it in action?
Tell us the process you want to automate — we'll show you the platform on it.
Or call +91 95525 86428
Runs on what you already trust
Splashgain is a partner of both Google Cloud and Microsoft Azure. Google Kubernetes Engine already carries exams at national scale, agent and automation workloads run on DigitalOcean and n8n, and the platform meets your stack through documented APIs rather than a migration.
Multi-cloud by design
Google Cloud — partner
GKE runs up to 50,000 concurrent exams at 100% uptime; Vertex AI and Vision AI extend evaluation and proctoring
Microsoft Azure — partner
Azure compute and AI services running alongside Google Cloud
DigitalOcean
Containerized AI agents and automation services
n8n workflow engines
Self-hosted automation orchestrating agent workloads behind every product
Multi-provider S3 storage
Documents and recordings distributed across multiple S3-compatible providers to scale
MongoDB
Document store behind agent state, workflow runs and unstructured assessment data
BigQuery
Rolling out as the assessment analytics warehouse
Plugs into what you already run
REST API
Documented endpoints with webhooks
n8n
Self-hosted workflow automation
Make
No-code system-to-system automation
MCP
Model Context Protocol servers for AI assistants
WhatsApp Business API
Candidate and applicant messaging — reminders, status and results
Email automation
Transactional and bulk mail on Amazon SES — verification, reminders, results and follow-ups, sent and tracked by agents
CERT-IN certified, on infrastructure you can name
The platform runs multi-cloud on Google Cloud and Microsoft Azure with a MeitY-empanelled security audit behind it. Data residency, encryption and retention are configured per customer rather than assumed.
- CERT-IN certified security audit
- Encryption in transit and at rest
- Configurable residency and retention
Certified, not just claimed
CERT-IN Certified
The platform, packaged for what you run
Assessment, proctoring and evaluation
- Large-scale secure exams
- AI proctoring and onscreen marking
- Generative AI skill assessment
50M+Assessments delivered
Explore Eklavvya
Document verification and automation
- Extract and verify any document
- Government API integrations
- Workflow automation and audit trails
99.5%Extraction accuracy
Explore DocuExprt
Admissions and enrollment
- Forms, fees and payments
- Merit lists and seat allocation
- AI counseling agents
2M+Applications processed
Explore ePraveshPrefer to see the agents on their own? Browse the AI employees and agent packs.
Before the demo
What is the difference between an AI agent and agentic AI?
An AI agent is one worker: it takes a goal, picks a tool, does a step and reports back. Agentic AI is the system around several of them — decomposing a goal into steps, handing work between agents, holding state across a process that runs for days, and rolling back cleanly when a step fails. One agent answers an admission query. An agentic system runs the admission round.
Is this just a chatbot with a different name?
No. A chatbot returns text and leaves the work to you. These agents write to the systems you already run — verifying a document, releasing a result, escalating a ticket — inside permissions you set, with every action logged and reversible. If it can only talk, it is not an agent.
Free presentation · 13 slides · PDF
Take the deck to your leadership team
The presentation we walk boards and CXOs through — thirteen slides on what deploying AI agents actually involves, from the roles to the guardrails to the commercials.
- 22 AI employee roles across 9 departments
- Eight department packs, and the agents inside them
- One day from first conversation to one agent live
- Three commercial models, and what each includes
Download the deck
No cost. Work email and organisation only.
Talk to us about the process you want to automate.
Tell us what you run today. We will show you what the platform does with it.
Book a Demo
Or call +91 95525 86428