Portfolio Background
Accepting two engagements this quarter

We Solve Problems, Not Just Write Code

We build AI powered Solution for construction firms, academic institutions, restaurants, and SaaS companies, taking each one from idea to a system that's actually live.

01 · Founder
Akash Kushwah, Founder & CEO of So Efforts Solution

Akash Kushwah

Founder & CEO

Building AI systems that automate operations.

At So Efforts Solution, we build practical AI, automation, and custom software systems designed around measurable business needs.

Proven Impact

AI platforms used by PhD researchers

₹50L+ construction losses recovered

400+ leads processed through automation

Enterprise RAG assistants built

02 · Websites We’ve Designed
7 Projects
Page 1 of 1
03 · Capabilities

What we build.

Purpose-built digital products engineered to create measurable business outcomes.

Five focused practices designed to move revenue, efficiency, automation, and customer experience forward.

01

AI Automation Systems

n8n workflows, OpenAI integrations, process automation.

For Operations teams drowning in repetitive tasks.
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02

RAG & LLM Systems

Document intelligence, knowledge bases, AI chatbots.

For Companies with thousands of documents and no search.
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03

Full-Stack SaaS Platforms

Multi-tenant apps with auth, billing, dashboards, AI features.

For Founders launching AI-powered products.
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04

Custom CRM Solutions

Lead management, automation pipelines, analytics.

For Sales teams needing control, not complexity.
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05

Real Estate Tech

Property platforms, lead gen tools.

For Builders, agents, and property managers.
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06

Restaurant QR Ordering Systems

Digital QR menu scanning, table ordering, kitchen dashboard, waiter-free ordering.

For Restaurants, cafés, Bars, and food courts.
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04 · How We Work

From discovery to a system running on autopilot.

A proven framework that transforms ideas into production-ready systems with measurable business impact.

01

Discovery

A 45-minute deep dive into your pain points, current tools, and success metrics.

02

Architecture Plan

Tech-stack recommendation, milestone breakdown, timeline, and investment outline.

03

Rapid MVP

A working prototype in 2–3 weeks. See it, test it, refine it.

04

Iterate & Scale

Tight feedback loops until the system runs your operation — not the other way around.

05 · Selected work

Work that delivers, not just looks good.

Each engagement framed as Problem → Solution → Outcome with measurable business impact.

EdTech · Research

AI Research Co-Pilot

Client · AI Research Education

Problem

PhD scholars spent months refining research topics, and proposals reportedly faced multiple rounds of rejection. Supervisors also spent significant time providing repetitive guidance.

Solution

An integrated AI research workspace featuring topic refinement, literature review assistance with citation mapping, proposal building, methodology recommendations, and scholar workspace versioning.

Stack

Next.js · Node.js · PostgreSQL · GPT-4 · LangChain · RAG · Vector Search

Akash built exactly what I envisioned, an AI co-pilot for my scholars.
— AI Research Education
View case study →
85%
First-submission approval rate (reported)
3 days
Topic refinement time (reported)
−60%
Supervisor guidance hours (reported)
50+
Active research projects (reported)
Construction · Legal Operations

ConstructIQ: AI Construction Delay Recovery

Client · Mid-size construction firm, India

Problem

Construction delays can create substantial financial losses. Relevant contract clauses, delay evidence, and claim opportunities can be difficult to identify across lengthy project documents.

Solution

An integrated construction intelligence system featuring contract analysis, delay cause identification, recovery calculations, jurisdiction-aware notice drafting, and a real-time project health dashboard.

Stack

Next.js · FastAPI · PostgreSQL · GPT-4 · LangChain · OCR · PDF Parsing

ConstructIQ found recovery opportunities our legal team missed for two years.
— Project Director
View case study →
₹50L+
Potential recoverable costs identified (reported)
15 min
Legal notice drafting time (reported)
92%
Delay-cause identification accuracy (reported)
3×
Project manager productivity (reported)
B2B SaaS · Knowledge Management

Enterprise RAG Chatbot: Document Intelligence

Client · B2B SaaS Company

Problem

Large collections of internal documents make it difficult for employees to find accurate information quickly. Repetitive support questions and lengthy onboarding can reduce operational efficiency.

Solution

A retrieval-augmented generation (RAG) chatbot with PDF, DOCX, and email ingestion, semantic search using pgvector, AI-generated answers with citations, and an administration panel for access management and logs.

Stack

FastAPI · PostgreSQL · pgvector · OpenAI · LangChain · React · Docker

It feels like every employee has a 10-year veteran sitting next to them.
— Operations Head
View case study →
3 weeks
Employee onboarding time (reported)
−65%
Support ticket volume (reported)
94%
Search accuracy (reported)
<2 min
Document processing to availability (reported)
Internal · CRM & Automation

So Efforts CRM: Lead Management Automation

Client · So Efforts Solution Pvt. Ltd. · Internal Project

Problem

Lead information was spread across spreadsheets, inboxes, and enquiry forms. Managing follow-ups manually made it harder to maintain consistent communication and track sales opportunities.

Solution

A custom CRM featuring centralized lead management, automated follow-up workflows, sales pipeline tracking, and analytics, with greater control over business data and workflow customization.

Stack

Next.js · PostgreSQL · n8n · OpenAI

View case study →
400+
Leads tracked and managed (reported)
0 hrs
Manual follow-up effort (reported)
Same-day
Lead response time (reported)
35%
Lead conversion improvement (reported)
Hospitality · Restaurant Technology

Spice Palace: QR-Based Restaurant Ordering

Client · Restaurant Chain

Problem

Manual order-taking can increase staff workload, slow down the ordering process, and limit opportunities to recommend additional menu items during dine-in service.

Solution

A digital restaurant ordering system featuring QR-code menu access, table-based ordering, intelligent upsell prompts, kitchen order routing, and order analytics.

Stack

Next.js · Supabase · Stripe · Tailwind CSS

View case study →
+30%
Average order value improvement (reported)
−50%
Order-taking staff workload (reported)

Technologies We Use

Ready to Start Your Project?

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