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The capabilities behind the products

Everything on this page is how we build. Today it ships as three products: Salient 1.0, the reasoning engine; Umpire, the governor for AI agents; and Verity, the control room across the apps you already run.

▸ CAPABILITIES

We do four things
exceptionally well.

And we do them all the way — from research to training to production deployment. No hand-offs to a different vendor. No "that's outside our scope."

01 · PILLAR

Custom-Trained LLMs

Not fine-tuned demos. Production models.

We take foundation models and reshape them around your specific domain — your documents, your workflows, your voice, your constraints. From supervised fine-tuning to preference optimization to self-improvement loops, we pick the method that fits the problem, not the trend.

▸Domain-specific supervised fine-tuning
▸Preference optimization (DPO, rejection sampling)
▸Retrieval-augmented generation pipelines
▸Evaluation frameworks tailored to your KPIs
▸Continuous improvement loops post-deploy
▸Deploy anywhere — cloud, on-prem, edge
02 · PILLAR

Bespoke AI Products

End-to-end products with AI at the core.

We build the complete thing. Backend, frontend, mobile, the ML infrastructure underneath, and the human-in-the-loop tooling on top. Our portfolio spans radiology, education, entertainment, fashion, finance, and fitness — and every product was built from zero, not assembled from templates.

▸Full-stack web and mobile applications
▸iOS, Android, Windows, macOS, Linux targets
▸XR products for Meta Quest and ARCore
▸WhatsApp-native AI assistants
▸On-device inference where privacy demands it
▸Scalable backend with observability built in
03 · PILLAR

Multi-Agent Systems

Orchestrated intelligence that actually executes.

Single-model assistants hit a ceiling fast. We design multi-agent architectures where specialized agents collaborate under an orchestrator, with explicit human oversight at the decisions that matter. The result is systems that plan, execute, and verify their own work.

▸Agent orchestrator design
▸Specialist sub-agent development
▸Tool-use and function-calling integrations
▸Safe autonomous execution with human checkpoints
▸Cross-agent memory and context sharing
▸Production-grade observability per agent
04 · PILLAR

Applied Research

Research that ships.

Computer vision for specialized domains. Synthetic data generation for rare classes. Novel evaluation frameworks. Retrieval methods beyond vanilla RAG. We do the research others publish about — and then we turn it into something that runs in production.

▸Medical imaging (segmentation, detection, VLM)
▸Document understanding and extraction
▸Speech recognition in Indian languages
▸Synthetic data for data-scarce domains
▸Factuality verification and hallucination guards
▸Custom evaluation harnesses
▸ WHY WE'RE DIFFERENT

Three things we refuse to compromise on.

Tailored, not templated

Every engagement starts from the problem. No reskinned generic assistants.

Built for India, and beyond

Multilingual by default. WhatsApp-native. Regional context baked in where it matters.

Privacy-first by design

DPDPA-aware. On-device inference when the data demands it. No training on your data without consent.

▸ INDUSTRIES

Who we've built for.

Healthcare
Radiology · Hospitals · Diagnostics
Education
Competitive exams · Gamified learning
Entertainment
Cinema · Gaming · Content generation
Fashion
Styling agents · Heritage-aware AI
Fitness
Form analysis · Regional nutrition
Finance
Autonomous trading · Risk management
Hospitality
Guest experience · Operations
Your industry
Let's talk about it
▸ HOW WE WORK

Five steps. No theater.

01

Scope

A 30-minute call to understand the problem, constraints, and what success looks like. We walk out with a proposal or we walk away — no filler.

02

Design

We map the data, the model, the product surface, and the deployment target. No slideware — working architecture, risk-ranked.

03

Build

Zero-planning, 100%-execution delivery sprints. Daily visibility. Honest progress — not status theater.

04

Ship

Deploy to production with observability, evaluation, and a clear rollback plan. Hand-off or managed — your choice.

05

Evolve

Models decay. Data drifts. We can keep the system sharp with continuous improvement loops and periodic re-training.

Got a problem worth building for?

Send us the outline. We'll come back with a scoped response within 48 hours.

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