A specialist AI and ERP-engineering firm
We embed elite AI talent inside growth-minded companies, delivering production-grade systems that stay secure, scale effortlessly, and deliver ROI fast. Founded in 2019, remote-first, and working as part of our clients’ teams across US and UK hours.
2019
founded, and building AI ever since
37
AI agents running live across four of our own products
3
major clouds, all of them in production
At a glance
- Founded
- 2019. Refocused on generative AI in 2023. Dynamics 365 optimization lead since mid-2026.
- Founder & CEO
- Mudassir Marwat, hands-on engineering leadership.
- Model
- Remote-first, embedded with clients' teams, US and UK hours.
- Clients in
- US, UAE, UK and Pakistan.
- Guiding principle
- If it doesn't run in production, it doesn't count.
Turning AI hype into hard-edged value
The company in its own words, unedited.
Cognilium AI is a specialist AI and ERP-engineering firm turning AI hype into hard-edged value for market leaders. We embed elite AI talent inside growth-minded companies, delivering production-grade systems that stay secure, scale effortlessly, and deliver ROI fast.
Cognilium works with manufacturers, distributors, retailers and scale-ups to transform fragmented business data into intelligent, margin-driving operations: agentic Generative-AI systems, LLM-powered data workflows, and full-stack SaaS product development, executed by embedded engineering teams and built in tandem with Microsoft Dynamics 365, SAP and modern ERP platforms.
By combining deep product thinking with applied-AI research, we help businesses quote faster, price smarter, and lead their markets with responsible, insight-driven AI inside the systems they already run. Our goal is simple: make Cognilium the trusted name in AI-powered ERP optimization for the next generation of market leaders.
Most AI ends in a slide deck. Ours ends in production.
The substance behind the paragraph above, in the same three parts file 01 puts it in.
Cognilium exists because most teams that want AI end up with slide decks and prototypes that never ship. The whole discipline is the opposite: design for reliability, cost and measurable outcomes from day one, deliver in weeks, and ship every system with the dashboards, documentation and support that let the client's team run it with confidence.
The company built its own products first, for recruiting, customer support, sales and legal, and turned those proven patterns into client work. That builder-operator heritage is the credibility: the approach is proven on real systems, not theory.
Since mid-2026 the sharpened lead is AI inside and beside the enterprise systems a business already runs. An ERP records and manages a process; it cannot optimize the decisions inside it. The optimal price, the optimal pick path, the optimal stock level, the last 20% where the margin lives, is what Cognilium builds. The ERP core is never touched; it is surrounded with intelligence. That makes Cognilium a complement to a customer's Dynamics implementation partner, never a competitor.
Built first, on ourselves
Cognilium AI builds the decision layer beside Microsoft Dynamics 365.
Dynamics is your system of record. Cognilium is your system of intelligence.
What we are for, and where it goes
Two sentences the company has to keep answering to.
Mission
Give product, operations and data teams AI systems they can run every day: faster decisions and less tedium, without giving up control, security or cost discipline.
Vision
Trustworthy, observable AI systems powering everyday products and operations, delivered with the speed and reliability of modern cloud software.
“If it doesn’t run in production, it doesn’t count.”
Five, and they decide arguments
The operating style underneath them is calm speed: fast but structured, ambitious but repeatable.
Reliability as a feature
Monitoring, runbooks and support built in from day one, not bolted on.
Builder DNA
Leaders who build, ship and document. People who think like founders.
Proof over hype
Real numbers with context; conservative, defensible claims only.
Ethical, responsible AI
Data protection, access control and explainability in every design.
Long-term partnership
Present after launch, with knowledge transfer and shared ownership of outcomes.
Two lanes, and one of them has a tell
If the second box below describes something that happens in your business every week, this page is about you.
Dynamics optimization
Mid-market manufacturers, distributors and retailers already running Dynamics 365, most often Business Central, who have the ERP working and now want better decisions out of it.
The tell
Someone in the business exports ERP data into a spreadsheet to make the real call: the planner rebuilding safety stock, the pricing manager approving discounts by rule of thumb, the quote desk re-typing customer emails.
AI engineering
Founders, CTOs, VPs of Engineering, Heads of Product, and operations and data leaders. Startups that need to ship AI fast, and enterprises that want AI added to existing systems with proper security and governance.
What they ask for
Agents that do real work, answers drawn from a company's own data, document intelligence, and voice, built to run in production rather than to demo.
Industries delivered in
- FinTechfamily office, financial advisory
- Legalcontract intelligence
- E-commerce and retailprice intelligence, marketplace monitoring
- Manufacturing, automotive parts and distributionERP, warehouse, quoting
- SaaS
- Recruiting and HR
- Sales and customer support
- EducationK-12
Ten capabilities, in the order they matter
The first is the lead. The other nine are the practice that makes the first one credible, and every one of them has shipped.
ERP AI and optimization apps
The lead. AI built beside Microsoft Dynamics 365, with delivered work on Odoo and patterns extending to SAP: quoting, pricing, pick-path and slotting, demand and inventory, contract review. Copilots and plain-language answers over ERP data.
Explore 02AI agents and multi-agent systems
Assistants that do real work, use tools and data, and know when to hand off to a human.
Explore 03Enterprise search and retrieval
RAG, GraphRAG on knowledge graphs, NL2SQL. Sourced, access-controlled answers over a company's own documents and data.
Explore 04Document intelligence
Read, classify, extract and validate contracts, financial documents and forms, with evidence-based confidence.
Explore 05Voice AI
Real-time, low-latency, multilingual voice assistants for sales, support and screening.
Explore 06Data engineering and pipelines
The clean, reliable data foundations AI runs on, batch and real time.
Explore 07Large-scale web scraping and price intelligence
High-volume collection from sites that actively resist it, turned into clean, searchable feeds.
Explore 08Cloud architecture and DevOps
AWS, Azure and GCP, with infrastructure as code, monitoring and cost discipline.
Explore 09SaaS and product engineering
Full end-to-end builds: front end, back end, AI.
Explore 10Talent Cloud
Staff augmentation. Pre-vetted AI engineers embedded in a client's team within days, month to month.
ExploreDiagnose, architect, deploy, optimize
Scope is agreed before anything is built, and what done means is agreed before that.
Diagnose
Scope before building.
Architect
Architecture and acceptance criteria agreed up front.
Deploy
Milestones tied to working software, weekly demos, replies within hours. Working proof of concept in days, production in about three weeks.
Optimize
Every deployment ships with documentation, dashboards, runbooks and training, plus post-launch support.
The standard way to start
A scoped four-to-six-week pilot on one workflow, with a single explicit success metric agreed up front and a weekly readout. No throwaway code: the pilot is the first production slice.
Engagement models
- Embedded solo engineer
- Cross-functional pod
- Dedicated enterprise team
Fixed-price, hourly, or retainer.
The stack, at a glance
The shape of it here, and the reasoning for every choice on the technology page.
Cloud
AWS-first for new builds, Azure-native for Microsoft-ecosystem and ERP work, GCP for the Google AI stack. All three run Cognilium systems in production, each with infrastructure as code.
Models
OpenAI, Anthropic Claude, Google Gemini, plus open and on-premise models.
Agents and knowledge
LangGraph, CrewAI, Google ADK, AWS Bedrock AgentCore, MCP. Neo4j GraphRAG, vector search, hybrid retrieval.
Voice and Dynamics
Twilio, LiveKit, Deepgram, ElevenLabs, Whisper. Dynamics work runs on the customer's own governed stack: Power Platform, Dataverse, Azure.
Open architecture, no vendor lock-in. Clients keep full ownership of code and data.
What we do, and what we will not claim
The second half of that heading is the part most pages leave out.
- Secure-by-design and least-privilege.
- Encryption in transit and at rest.
- Role-based access.
- Audit logging.
Compliance alignment
Architectures aligned with SOC 2, ISO 27001, GDPR, HIPAA and PCI-DSS practices.
Aligned with. Cognilium does not claim formal certification.
Mudassir Marwat
Hands-on engineering leadership. He founded Cognilium AI in 2019, refocused it on generative AI in 2023, and set the Dynamics 365 optimization lead in mid-2026. The guiding principle on this page is his, and it is the standard every engagement is held to.
“If it doesn’t run in production, it doesn’t count.”
Everything a first call usually covers
Every answer is in the page source rather than behind a click, because the systems that summarise this page never click anything.
What is Cognilium AI?
Cognilium AI is a specialist AI and ERP-engineering firm, founded in 2019. It builds AI systems businesses run every day: agents that do real work, answers drawn from a company's own data, document intelligence, and voice. Its sharpest current direction is AI inside the ERP, as optimization apps that work in tandem with Microsoft Dynamics 365.
What is the founding story of Cognilium AI?
Cognilium AI was founded in 2019 by Mudassir Marwat, refocused on generative AI in 2023, and has led with Dynamics 365 optimization since mid-2026. The company built its own products first, for recruiting, customer support, sales and legal, and turned those proven patterns into client work. That builder-operator heritage is the credibility: the approach is proven on real systems, not theory.
What is Cognilium AI's mission?
To give product, operations and data teams AI systems they can run every day: faster decisions and less tedium, without giving up control, security or cost discipline. The vision behind it is trustworthy, observable AI systems powering everyday products and operations, delivered with the speed and reliability of modern cloud software.
Does Cognilium AI replace or compete with a Dynamics 365 implementation partner?
No. An ERP records and manages a process; it cannot optimize the decisions inside it. Cognilium builds the optimal price, the optimal pick path and the optimal stock level, which is the last 20% where the margin lives. The ERP core is never touched; it is surrounded with intelligence. That makes Cognilium a complement to a customer's Dynamics implementation partner, never a competitor.
What types of companies work with Cognilium AI?
Two lanes. Mid-market manufacturers, distributors and retailers already running Dynamics 365, most often Business Central, who have the ERP working and now want better decisions out of it. And founders, CTOs, VPs of Engineering, Heads of Product, and operations and data leaders: startups that need to ship AI fast, and enterprises that want AI added to existing systems with proper security and governance. Clients are in the US, UAE, UK and Pakistan.
Which industries has Cognilium AI delivered in?
FinTech, in family office and financial advisory. Legal, in contract intelligence. E-commerce and retail, in price intelligence and marketplace monitoring. Manufacturing, automotive parts and distribution, in ERP, warehouse and quoting. SaaS. Recruiting and HR. Sales and customer support. And education, at K-12 level.
How does a project with Cognilium AI start?
With a scoped four-to-six-week pilot on one workflow, with a single explicit success metric agreed up front and a weekly readout. No throwaway code: the pilot is the first production slice. The method around it is Diagnose, Architect, Deploy, Optimize, with architecture and acceptance criteria agreed before building, milestones tied to working software, a working proof of concept in days and production in about three weeks.
What engagement models does Cognilium AI offer?
An embedded solo engineer, a cross-functional pod, or a dedicated enterprise team, on a fixed-price, hourly or retainer basis. The company is remote-first and works as part of clients' teams across US and UK hours.
What is Cognilium AI's security and compliance posture?
Secure-by-design and least-privilege, with encryption in transit and at rest, role-based access and audit logging. Architectures are aligned with SOC 2, ISO 27001, GDPR, HIPAA and PCI-DSS practices. Aligned with: Cognilium does not claim formal certification.
Who is the founder of Cognilium AI?
Mudassir Marwat founded Cognilium AI in 2019 and leads it as CEO with hands-on engineering leadership. The company's guiding principle is his: if it doesn't run in production, it doesn't count.