AI-native B2B marketplaces with a procurement assistant and a self-enriching catalog
Trusted by 100+ innovative teams
What we build
An AI procurement assistant helps buyers find the right suppliers and products, drafts requests for quotation, and matches specifications. The catalog cleans and enriches itself, and search understands what buyers actually mean. The result is a marketplace that does the heavy lifting of B2B buying, not one that just lists products.
Built for teams like yours
What you'll get
Buyers describe what they need in plain language, and the assistant finds matching suppliers and products, compares specifications, and shortlists, instead of buyers digging through endless catalogs. It turns a vague requirement into a short, sensible set of options.
The assistant drafts a request for quotation from a buyer requirement and helps sellers respond, cutting the slow back-and-forth that stalls B2B deals. Comparisons, revisions, and conversion to an order are handled in one flow.
AI standardises messy supplier data, fills gaps, categorises products, and matches equivalents, so the catalog stays searchable and trustworthy as vendors come and go. You stop paying people to tidy spreadsheets.
Buyers rarely use your exact part names. Semantic search understands meaning, so a request for a ten millimetre stainless bolt finds the right SKU even when the listing is worded differently.
AI helps a new vendor map their catalog to your structure in hours instead of weeks, so your marketplace grows without a manual bottleneck slowing every new seller.
Analytics on what buyers search, request, and abandon let you and your vendors price and stock with evidence, not guesswork, and spot demand before it shows up in revenue.
Applications
See how teams like yours are putting b2b marketplace platform development to work.
Connect distributors and business buyers with bulk pricing, credit terms, and reordering built for repeat, high-volume purchasing.
Let manufacturers sell straight to businesses with spec-driven catalogs and RFQ workflows, without a layer of intermediaries.
Handle deep, specification-heavy catalogs where buyers must match exact parts, which is where semantic search and the assistant earn their keep.
Give a large buyer a private marketplace of approved suppliers, with approval chains, budgets, and ERP integration.
Run an open marketplace with many sellers and buyers, vendor verification, commissions, and payouts.
How we deliver
We map your buyers, sellers, catalog structure, and the buying workflows that matter, then scope a focused first version that proves value quickly.
We build vendor management, the catalog, RFQ and ordering, payments, and the buyer and seller portals on a stack that scales.
We add the procurement assistant, catalog enrichment, and semantic search, grounded in your real catalog and kept under human approval for quotes and pricing.
We go live, watch what buyers search and abandon, and keep tuning the catalog, the matching, and the assistant on real usage.
Tech Stack
We choose the right tools for your specific needs, not just what's trending. Our stack is battle-tested across hundreds of production deployments.
Plain-language
buyer search and discovery
Hours
to onboard a vendor catalog, not weeks
One
platform for catalog, RFQ, orders, and payments
B2B Marketplace Platform Development Implementation
Use the same rollout pattern we apply in production programs: architecture review, risk controls, and measurable milestones from pilot to scale.
4-8 weeks
pilot to production timeline
95%+
delivery milestone adherence
99.3%
observed SLA stability in ops programs
Deep dive
B2B Marketplace Platform Development is a core capability at Boolean & Beyond. We don't just implement technology — we engineer complete solutions that solve real business problems. Our team in India combines deep technical expertise with practical business understanding to deliver systems that work in production, not just in demos.
We have delivered similar solutions for startups, scale-ups, and enterprises across fintech, healthcare, e-commerce, manufacturing, and SaaS platforms — handling real-world complexity at scale.
End-to-end architecture design that balances performance, maintainability, and cost. We start with your business requirements and work backward to the technology, not the other way around. Every solution includes automated testing, CI/CD pipelines, monitoring, and documentation.
AI-first approach where applicable: we integrate LLMs, computer vision, voice AI, and recommendation engines into business workflows. But we only add AI where it delivers measurable value — not every problem needs a neural network.
Our integration patterns connect with your existing systems: REST/GraphQL APIs, database connectors, message queues, and webhook-based event architectures. We build alongside your stack, not on top of it.
Our standard stack: TypeScript + Next.js for web applications. Python + FastAPI for AI/ML services. PostgreSQL with pgvector for data + vector search. Redis for caching and real-time features. Kubernetes on AWS/GCP for deployment. Prometheus + Grafana for observability.
We choose tools based on your specific constraints — team expertise, existing infrastructure, compliance requirements, and budget. No one-size-fits-all architecture.
For AI-powered features, we implement proper guardrails from day one: input validation, output filtering, hallucination detection, cost controls, and human-in-the-loop workflows for high-stakes decisions.
Discovery Sprint (Week 1-2): Requirements deep-dive, architecture design, and technical spec. You get a clear picture of what we'll build, how it works, and what it costs — before writing a line of code.
Build Sprint (Week 3-8): Iterative development with weekly demos. You see progress every week, provide feedback, and steer the direction. No big-bang reveals after months of silence.
Launch Sprint (Week 9-10): Performance optimization, security hardening, monitoring setup, and production deployment. Team training and documentation handover.
Post-Launch: We don't build and disappear. Ongoing support, optimization, and feature development as your needs evolve. Our retainer clients get priority response and dedicated engineering hours.
Our implementations have delivered measurable business impact: 40% reduction in manual processing time through AI automation. 35% improvement in customer engagement through personalized experiences. 60% cost savings on infrastructure through architecture optimization. 90-day time-to-market for MVPs using our SPRINT framework.
We bring senior-level engineering talent at competitive rates. Our team includes architects with 10+ years of experience building production systems, not junior developers following tutorials. We take ownership of outcomes — your success is our success.
Every engagement starts with a clear scope, timeline, and investment. No scope creep, no surprise bills, no "we need just one more sprint" conversations. If we discover complexity during development, we flag it immediately and discuss options.
Book a free 30-minute technical consultation. Bring your hardest problem — we'll give you an honest assessment of how we'd solve it, realistic timelines, and a clear next step. No sales pressure, just engineering expertise.
Fintech: Automated compliance checking, fraud detection pipelines, and intelligent document processing for KYC/AML workflows. We build systems that process thousands of applications daily with 95%+ accuracy.
Healthcare: Clinical decision support, patient communication automation, and medical record analysis. HIPAA and DPDP Act compliant architectures with proper audit trails.
E-Commerce: Personalized recommendation engines, semantic product search, dynamic pricing algorithms, and conversational shopping assistants that increase conversion by 20-35%.
Manufacturing: Computer vision quality inspection, predictive maintenance models, and production scheduling optimization. Edge deployment for real-time factory floor decisions.
Fixed-scope projects: Clear deliverables, timeline, and investment. Ideal for well-defined features or MVPs. You know exactly what you get and what it costs before we start.
Dedicated team: 2-6 engineers embedded in your workflow for ongoing development. Sprint-based delivery with weekly demos. Scale up or down based on your roadmap.
Technical advisory: Architecture review, technology selection guidance, and hands-on mentoring for your team. Ideal when you have developers but need senior technical direction.
How long does a typical project take? MVPs in 6-8 weeks, production features in 8-12 weeks, enterprise platforms in 3-6 months. We use 2-week sprints with weekly demos so you see progress continuously.
What does it cost? Projects range from ₹10 lakhs for focused integrations to ₹50+ lakhs for full platform builds. We provide detailed estimates after the discovery sprint — no surprises.
Do you support post-launch? Yes. Most clients transition to a maintenance retainer (₹2-5 lakhs/month) for ongoing optimization, bug fixes, and feature additions. We don't build and disappear.
B2B buying is not like dropping a product into a cart. A single purchase can involve a specification, several suppliers, a request for quotation, a negotiation, credit terms, and sign-off from more than one person. Multiply that across thousands of SKUs and a roster of vendors whose data never quite matches, and the friction is enormous.
Most B2B marketplaces simply digitise the catalog and leave the hard parts to people. An AI-native marketplace takes on the heavy lifting: helping buyers find the right thing, drafting the paperwork, and keeping a messy, multi-vendor catalog clean and searchable.
Behind the AI, this is a complete B2B marketplace. Here is what it covers.
Onboard, verify, and manage sellers, each with their own dashboard, catalog, and performance score. Approval workflows, commission rules, and payout handling keep a many-vendor marketplace under control as it grows.
Manage SKUs at scale with bulk uploads, variants, units of measure, and tiered or customer-specific pricing. AI standardises and enriches incoming vendor data so the catalog stays consistent no matter who uploaded it.
Buyers raise requests for quotation, sellers respond, and the platform manages bids, comparisons, revisions, and conversion to orders. The assistant drafts both the request and the response to speed the cycle up.
Role-based dashboards for each side, with order history, approvals, documents, and analytics, so buyers and vendors self-serve instead of trading emails.
High-volume ordering, blanket purchase orders, reorder from history, and scheduled recurring orders, built for the way businesses actually buy.
Trade credit, payment terms, and credit limits, with payment gateway and invoicing support, plus integration into ERP and accounting systems like SAP and Tally so orders flow into the tools you already run.
Under the hood, the procurement assistant uses retrieval-augmented generation, or RAG, over your catalog and supplier specifications. When a buyer describes a need, the system retrieves the closest-matching products and a large language model, an LLM, explains the options and drafts the request for quotation. Semantic search means a buyer finds the right item even when their wording does not match your part names. The assistant itself is an AI agent that can search the catalog, compare specifications, and shortlist, while the same generative AI cleans and enriches messy vendor data as it arrives.
Powerful does not mean unsupervised. The assistant works from your real catalog and supplier data, not the open internet, and it shows the products and specifications behind every suggestion so buyers can verify. Quotes, credit decisions, and pricing changes stay under human approval, because they carry commercial and legal weight. And because catalog, pricing, and customer data are commercially sensitive, the platform can run inside your own environment with clear control over who sees what.
It uses retrieval-augmented generation, or RAG, over your catalog and supplier specifications. When a buyer describes what they need, it retrieves the closest matches and a language model explains the options and drafts the request for quotation, with the products and specs shown so the buyer can check.
Yes. AI standardises, categorises, and enriches incoming vendor data and matches equivalent products, so the catalog stays clean and searchable even when every supplier formats data differently.
Yes. Orders, invoices, and inventory can flow into ERP and accounting systems such as SAP and Tally, so the marketplace fits your existing back office.
Yes. Buyers and sellers each get their own role-based portal with the dashboards, documents, and workflows relevant to them.
No. It recommends and surfaces evidence, but pricing, quotes, and credit decisions stay under human approval because they carry commercial weight.
Yes. It supports Indian tax and invoicing needs, multi-currency for cross-border trade, and B2B credit terms and limits.
Yes. Your data stays yours, and the platform can be deployed inside your own cloud environment where privacy or residency require it.
A focused pilot is typically live in a few weeks, with the full marketplace scaling from there.
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Delivery available from Bengaluru and Coimbatore teams, with remote implementation across India.
Case Studies
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Boolean and Beyond
825/90, 13th Cross, 3rd Main
Mahalaxmi Layout, Bengaluru - 560086
590, Diwan Bahadur Rd
Near Savitha Hall, R.S. Puram
Coimbatore, Tamil Nadu 641002