Enterprise AI, in production.

Agentic systems, document intelligence, and decision engines that we design, ship, and operate.

★ Agenda

1. The AI maturity gap

2. What can we do for you

3. Proof in production

4. Next steps

The AI maturity gap

Most Enterprise AI never leaves the prototype and sets bad precedents

•

POCs are simply a beginning. The work that follows is where the ROI lives: data access, evaluation, security review, change management, and rollouts.

•

Pilots stall when outcomes are unclear and nobody owns the path from launch to reality.

•

Companies need to make the uncomfortable jump from a model that works in a sandbox to a service that holds up under real traffic.

95%

of enterprise GenAI pilots deliver no measurable P&L impact

MIT NANDA, 2025

80%+

of AI projects fail. About twice the rate of non-AI IT projects

RAND, 2024 ⋅ Updated 2025

50%+

of GenAI projects are abandoned after the proof of concept

Gartner, 2026 (reinforced from 2024)

Maturity shows up in production.

So we build it in from the first sprint, then stay to operate it.

Production

Runs under real load

Systems with evaluation and monitoring loops, not one-off outputs.

How we deliver

Evals, observability, scale-friendly design, and security from the first sprint.

Governance

Governed by design

Explicit boundaries on what a model sees, where it runs, and who can audit it.

How we deliver

Decision engines, responsibility matrix, OWASP audits, corporate playbooks, etc

Ownership

Owned after launch

Someone is accountable when it breaks. AI for speed, humans for accountability.

How we deliver

Metrics and KPI tracking, feedback loops, A/B testing, on-call rotation support.

Leadership & Advisors

Swanand Pagnis

Founder & CEO

Experienced CTO and entrepreneur with 20 years in product engineering. Previously led global AI, B2B SaaS, and Fintech teams.

Luís Rodrigues

VP and Head of AI

Former CPTO at QuickCheck, Region Head at Lab49, Leading Digital Transformation Across FS, Telco & Government.

Advisors

Vikash Agarwal

General Counsel & Strategic Advisor

Deep PE, VC, Corporate Strategy, and M&A track record with brands like Oyo, IndusLaw, LinkLegal Associates

Shripad Agashe

Technology Advisor

Senior Engineering Leader at Intuit. Deep fintech and software scaling experience.

Ajey Gore

Technology & Strategic Advisor

Operating Partner at Peak XV and former Group CTO at GoJek

What can we do for you

Six building blocks

Most engagements combine a few of these.

🚡

Agentic workflows

Systems that plan and carry out complex multi-step work.

🗄️

Document intelligence

Review, redline, extract, and edit long, high-stakes documents.

🔮

Context infrastructure

Agentic memory, RAG systems, and tools for other agents to build on.

🎞

Multimodal AI

Images, video, voice, and 2-D/3-D, from generation to understanding.

🫆

Private & air-gapped AI

Runs where the data lives, when it can't leave the building.

⚡

Real-time decision engines

Compliance, business rules, and AI-assisted judgment under load.

These are also the building blocks of FreedomAI, the "BigTech" grade product we built.

Our IP

FreedomAI: Our product complement to enterprise engineering.

What Microsoft 365 Copilot should always have been: a model-agnostic layer that brings AI where work happens and in the tools you already use every day.

Editing & Summarization

Live

Drafts, edits, redlines, and comments, handled in place inside the document.

Rules & Compliance

Live

Validates work against corporate playbooks, brand guides, legal standards, and templates.

Research & Scoping

In progress

Searches across every linked project doc, follows cross-references, and cites its sources.

Cross-app Intelligence

In progress

Connects signals across Word, Excel, Outlook, and Teams into one shared context.

Context Continuity

Planned

Hands work between teammates, so anyone can pick up exactly where the last person left off.

Actions & Integrations

Planned

Decision engines, workflows, automations, and third-party connections that close the loop.

Model-agnostic across GPT, Claude, Gemini, and open models. A working proof of concept, benchmarked against Microsoft 365 Copilot. Private walkthrough on request.

Trusted by leading companies

Three pillars of our work

The standards behind every engagement.

Production-grade by default

Evaluations and tests, so quality is measured rather than assumed.

Observability into cost, latency, and accuracy once it is live.

Security and data-governance review before launch, not after.

Agentic depth, well beyond chatbots

Teams of agents that plan, call tools, and check their own work.

Built on industrial-strength SDKs from Anthropic and Vercel.

AI-native by design: we ship skill files, MCPs, harnesses, and more.

We fit the pattern to the task: sequential, parallel, or orchestrated.

Your data stays yours

Deploy in your cloud or on-prem, including air-gapped environments.

Clear boundaries on what each model and agent can read.

We ensure your team is able to run and extend the system.

Proof in production

Enterprise B2B SaaS

Corporate Real Estate planning & rebuild platform

Global team, Fortune 500 customers

AI-driven portfolio planning, occupancy planning

Fully automated building-code compliance

Challenge

Guideline mapping per project took about three weeks and broke as rules changed

Compliance checks depended on external auditors and ran for months

Core capital-projects work shipped on a timescale of a year or more

Engagement

Embedded agentic workflows (Agno, Vercel AI SDK) into the live platform

NLP guideline management that builds config from documents and plain language

Digital building-compliance that checks any strategy against regional codes

Impact

✓Customer onboarding went from about 1-month to < 1 day

✓Compliance review went from auditor-months to < 10 min per strategy

✓Capital-projects rebuild shipped in three sprints against a year-plus estimate

✓Helped land two Fortune 500 enterprises, including a global healthcare company

LegalTech SaaS

Lucio

Legal document platform

Competes with Harvey & Legora

An AI assistant inside Microsoft Word

Built for long, high-stakes documents

Challenge

Legal documents run past 200 pages and resist simple chat tools

Useful edits need full-document context, not snippets

The work has to happen inside Word, where the lawyers already are

Engagement

A Word add-in that reads and edits 200-plus page documents in place

AI indexing that holds context across the whole file

Contextual, multi-pass edits rather than one-shot answers

Impact

✓Deep edits and refinements across long documents

✓A native Word workflow, with no copy-paste between tools

✓Built for high-stakes professional review

✓Lucio went from a sophisticated dashboard to a SOTA LegalTech suite

✓Turn-around time for corporate playbook adherence went from days to minutes

Dubai Based Family Office

$1B+ AUM, $100m+ revenue family office in education and real estate, Dubai

16 years of legacy MS SQL systems

Data siloed across business lines

Challenge

Sixteen years of data locked in legacy SQL systems

Executives could not get answers without a developer

Pulling figures by hand took hours

Engagement

Full-scale AI Transformation

An ETL layer and a Text-to-SQL interface over the legacy data

Plain-English queries across school and real-estate metrics

Secure retrieval with context built for each domain

Impact

✓Stringent data silos allowed AI access to every employee

✓Reduced manual data extraction time from hours to seconds

Fast Growing Fintech Startup

Financial-advisory platform from India

Built on Ruby on Rails

Surfaces fees, performance, and gaps across mutual-fund portfolios

Massive virality on Reddit

Challenge

A strong analytical product with little automation on top

A monolith with no retries, circuit breakers, or multi-tenancy

Could not onboard banks and large portfolios at their scale

Engagement

Split the monolith into three multi-tenant microservices

Built an AI based 'what-if simulation engine' for human teams

Exposed the analytics product as an MCP server for the agents to query

Impact

✓AI-augmented relationship managers convey portfolio strategies to customers live on call

✓AI allows customers to run simulations using plain-language

✓Pilot adopted by several Indian banks, many of which became paid customers

✓Operations scaled from two people to hundreds of staff members

India's Premier EV Charging Platform

EV charging network and charger-management platform

Integrating with BHIM on the UPI network

"India-scale" traffic

Challenge

A production downtime incident led to trust erosion

Vertical scaling and tighter policies did not help

The BHIM integration would bring millions of daily users

Inconsistent AI integration demands from platform partners

Engagement

Diagnosed the query and connection problems and ended the firefight

Scaling fixes: Right-sizing, fixed pooling, and data indexes

Launched and validated fast AI POC prototypes

Impact

✓Data layer re-architected to sustain 10M daily active users

✓Holds up at close to a million requests per minute

✓Launched into production alongside the BHIM/UPI integration

✓Avoided shipping useless AI that does not do anything

Some more AI we have shipped

A sample of other production and pilot work from across our team. Happy to dive into specifics.

FinTech

Tradomatix

Real-time AI video support agent with photorealistic avatars and sub-1.5s voice.

WebRTCElevenLabsHeyGen

RegTech

ValidComms

Ad-creative compliance checker that validates mortgage marketing against regulatory guidelines.

ComplianceLangGraph

EdTech

Leap-Road

AI course-production suite: script, audio, review, and avatar video in one pipeline.

Multimodal

AutoTech

A major UAE auto-inspection platform, re-architected on AWS for roughly 200x throughput.

ArchitectureAWS

GovTech

Six-language emergency voice agent for a metro police line, handling 8–10K calls a day with automated incident reports.

VoiceTwilio

Real estate

Godrej Properties

Photorealistic AI property tours with a voice assistant for live questions.

3-DVoice

Entertainment

Amazon Prime Video

Personalized launch campaigns with custom video, voice, and interactive journeys.

MultimodalElevenLabsHiggsfield

Analytics

Self-serve analytics that lets business users query live data in plain English.

Text-to-SQL

Autonomous systems

Air-gapped model delivery and continuous retraining for autonomous vehicle fleets.

MLOpsEdge

Next steps

Start here

Start with a clear and fast proof of concept 🏎

Pick one workflow. We build it on your data and show it working, on a short and fixed scope.

•A workflow you choose. Scoped and clarified on a short call

•Built on agreed terms, our tools & our environment

•For our last client, we built the PoC over a weekend

•You keep the build and a clear path to production

Mutual commitment

You set the bar. If we clear, we proceed to production together.

Success defined up front, so the call to move forward is made before we even begin.

•You set the success metric before we start

•We clear it, and we move to a production engagement

•We miss, and you keep the build with nothing more owed

•Both of us get to avoid repeat cycles of we-send-you-review

We appreciate you coming in with a clear acceptance criteria and a high bar.

Why us

A small, elite team with AI maturity and a track record of staying to operate it.

🚀

In production

Real systems, real users. All the bells and whistles.

🤖

Agentic depth

Agent teams, tools, MCP, skills, far beyond mere chatbots.

🌍

Forward deployed

The globally emerging engagement model to get the best out of AI.

🛡️

Governed by default

Evaluation, observability, and data boundaries from day one.

💸

Capital-efficient

Small, senior-driven squads with high velocity and deep expertise.

🤝

Risk-reversal

Skin in the game, aligned incentives, outcome-driven.

📲

Let's Talk

• Swanand Pagnis

• swanand@superlinearinsights.com

• +971 56 865 1245

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