About Dailoqa: The Agentic AI, Native Engineering Company Built for Financial Services
Updated: Sep 29
Dailoqa is an AI-native, compliance-first agentic AI company. We build enterprise solutions exclusively for financial services. This article explains who we are, and what we do.
Key Takeaways
We founded Dailoqa in 2024, headquartered in London, to close the gap between what general-purpose AI could produce and what regulated financial services required.
We build agentic AI exclusively for financial services, not as a general-purpose AI product adapted afterwards.
Combined Intelligence, agentic AI running the process, humans owning judgment-heavy decisions, is the operating principle behind every use case we build.
The enterprise-grade Broccoli™ platform is our technology layer, built to be LLM-agnostic, secure by design and compliance-first.
We serve financial services institutions across the UK, India, UAE, Australia, ASEAN, Africa and Switzerland.
Responsible AI is architectural for us, defined agent scope, maker-checker separation and audit logging, not a stated value alone.
About Dailoqa?
Dailoqa is an AI-native, compliance-first agentic AI company. We build enterprise solutions using agentic AI for financial services, working with banks, wealth management firms, capital markets organisations and insurance businesses. This article covers what we do, how we combine agentic AI with native engineering, which financial services industries we serve, and what our enterprise-grade Broccoli™ platform is.
Why We Started Dailoqa
We founded Dailoqa in 2024, headquartered in London, as a group of financial services leaders and AI engineers who had each run into the same limitation in their own roles. General-purpose AI tools could produce a fluent, confident answer on a credit decision or a compliance question, but not one that would hold up to a regulator's or auditor's review.
What Does Dailoqa Do?
We build agentic AI systems for financial institutions, covering workflows such as onboarding, KYC review, credit assessment, transaction investigation, trade reconciliation and claims processing. Rather than offering a general-purpose AI product adapted for finance, we build our systems from the start around financial services compliance, oversight and audit requirements.
Our approach is built around Combined Intelligence, our operating principle for financial services. Agentic AI runs the process and coordination across a workflow, while people retain ownership of decisions involving risk, suitability, or regulatory judgment.
We build agentic AI systems purpose-built for regulated financial services workflows, not general-purpose AI adapted after the fact.
What Is Dailoqa's Vision?
We believe AI-native will become the default operating model for financial services, not a differentiator. Within the next several years, we expect institutions that treat agentic AI as core architecture, not a bolt-on feature, to set the pace on cost, speed and regulatory readiness, while institutions still adding AI features to legacy systems fall further behind.
Success, for us, is not measured only in the workflows we automate. Success means a financial institution can demonstrate, to its own board and to its regulators, exactly which decisions a machine made and which a person made, and why.
Combined Intelligence is not a phrase we attach to individual products. Combined Intelligence is the standard we hold the whole company to, agentic AI and human judgment working together deliberately, rather than one quietly replacing the other.
Our vision is AI-native as the default operating model for financial services, with Combined Intelligence as the standard we build every product against.
What Inspired Our Founders?
Dailoqa's founders bring backgrounds spanning global banking, financial services leadership and AI engineering.
Piyush Singh, Co-founder
Piyush is a senior consulting and technology leader with experience across APAC, Europe, the Middle East and Africa. At Accenture, he held senior roles responsible for major P&L portfolios, leading transformation programmes for global banks, the world's largest mortgage provider by volume, and a leading commercial insurer, with a particular focus on financial services. Before Accenture, he was a Sales and Management Board Member at Xansa. Piyush has been instrumental in architecting the AI-native business architecture underpinning Dailoqa's Broccoli™ platform, and continues to advise bank, wealth management and fintech boards on AI strategy and organisational transformation.
Arun Singal, Co-founder
Arun is a senior technology leader with over 30 years of experience supporting financial services clients across Europe, the US, Southeast Asia and South Africa. He has held senior delivery roles at TCS and Accenture, specialising in technology-enabled change, digital transformation and large-scale systems delivery for Fortune 500 clients. With a strong interest in emerging technologies, Arun has worked across data science, IoT, robotics and artificial intelligence, and continues to explore these areas through his startup, IR4Tech.
Priyanka Nayyar, Co-founder
Priyanka is a commercially focused HR leader with international experience across APAC and Europe. At Accenture, she held senior roles across technology, consulting and digital businesses, most recently as Workforce Transformation Lead for EMEA, where she led the firm's largest acquisition spanning Europe, Asia and North America. She has worked directly with management committees and boards on complex business challenges, including M&A, organisational design and large-scale transformation. Priyanka believes the most lasting impact comes from aligning people strategy with business goals, a principle that shapes how Dailoqa builds its own team and culture.
Beat Monerrat, Co-founder
Beat has over 30 years of experience leading large-scale transformation in exchanges and wealth management banking across Europe, the US and Asia. At Accenture, he shaped the firm's global consulting strategy, led consulting transformation across the company, headed the financial services business in Asia Pacific, and served as client lead for some of the world's largest banks. Since 2021, Beat has focused on investing, advising and board roles, backing ideas that challenge convention and find new ways to connect with customers.
Sanjay Salil, Co-founder
Sanjay is a serial entrepreneur, founder and CEO of MediaGuru, a media technology company, and IntellAI, which focuses on AI and quantum technologies. He has helped establish more than 50 media companies across Asia, the Middle East and Africa, and his teams have built products spanning banking, energy and education, including a personalised adaptive learning platform. A former broadcaster and news presenter, Sanjay is a recognised speaker and mentor in AI and media, and his work has been featured in publications including Business Standard, CNN, The Washington Post, Mint and The Wall Street Journal.
Why Is Dailoqa Focused on Financial Services?
Financial services workflows carry regulatory obligations, audit requirements, and judgment-based risk that general-purpose AI tools are not built to handle. We focus exclusively on financial services so every part of our platform is designed around what banks, wealth managers, capital markets firms, and insurers need to demonstrate to regulators and auditors.
A general-purpose AI model can produce a fluent, confident answer on a credit decision or a compliance question without understanding what counts as an acceptable answer in that specific context. Building exclusively for financial services means that context, risk appetite, product rules, and regulatory boundaries are designed into our systems rather than added as a review step afterwards.
Piyush Singh, our co-founder, has been directly responsible for architecting the AI-native business architecture underpinning Broccoli™, designing this separation of agent roles into the platform from the start.
Our exclusive focus on financial services means our systems are designed around regulatory and audit requirements from the start, not retrofitted onto general-purpose AI.
How Does Dailoqa Combine Agentic AI and Native Engineering?
AI-native engineering means we build our systems around agentic AI from the ground up, rather than adding AI features to existing software. Our engineering decisions are made with agentic behaviour and financial services compliance as the starting point.
In practice, this means giving each agent a specific role, a product, and a policy tailored to the particular context, rather than broad, shared permissions. We separate the agent responsible for preparing a recommendation from the agent or person who approves it, and keep an audit record for each agent's action instead of a single chat transcript for the entire workflow.
AI-native engineering means we build agentic behaviour and compliance requirements into the architecture from the start, not layer them on afterwards.
What Use Cases Does Dailoqa Offer?
Our agentic AI systems support workflows across the financial services value chain, wherever a process combines structured data, unstructured documents and a judgment-based decision point.
Onboarding and KYC review, including document verification and exception handling
Credit memo preparation and underwriting support
Transaction investigation and case-building for risk and compliance teams
Trade reconciliation across systems and venues
Claims processing, from first notice of loss through to assessment
Portfolio review support for wealth management teams
Our use cases span onboarding, credit, compliance, capital markets and insurance workflows, wherever structured data, documents and judgment intersect.
What Is Broccoli™ Agentic AI Platform?
The enterprise-grade Broccoli™ platform is our agentic AI platform for financial services, the technology layer that runs the multi-agent workflows described throughout this article. Broccoli™ is the platform, not the company. We built it to be LLM-agnostic and agentic-framework-agnostic, secure by design, compliance-first, and production-ready for financial services environments.
Broccoli™'s Multi-Agent Orchestration capability applies role, product, and context-specific agent policies, separates the agent that makes a recommendation from the one that checks it, and keeps an immutable audit trail of every agent action, the same controls a regulator would expect from a human team doing equivalent work.
Broccoli™ is built by a team with deep roots in enterprise AI and financial infrastructure engineering. Meet the people behind it further down this page.
Broccoli™ is our platform, built to be LLM-agnostic, secure by design and compliance-first for regulated financial services.
Which Financial Services Industries Does Dailoqa Serve?
We build for banks, wealth managers, capital markets firms and insurers, adapting the same underlying platform to the specific workflows and regulatory context each vertical requires.
Retail Banking
In retail and commercial banking, our systems support onboarding, KYC review, credit memo preparation and exception handling, work that combines document review with judgment calls a rules-based tool cannot make alone.
Wealth Management
In wealth management, our agentic AI assembles portfolio reviews from multiple data sources and flags rebalancing needs, while relationship managers retain approval over anything client-facing.
Capital Markets
In capital markets, our systems support trade reconciliation across venues with mismatched data formats, with a separate agent or operations analyst confirming genuine exceptions before treating them as breaks.
We adapt the same underlying platform to the specific workflows and regulatory context of each financial services vertical we serve.
Where Does Dailoqa Have a Presence?
We are headquartered in London and operate across the UK, India, UAE, Australia, ASEAN, Africa and Switzerland, working with financial institutions in markets with different regulatory regimes and different stages of agentic AI adoption.
Our presence spans the UK, India, UAE, Australia, ASEAN, Africa and Switzerland, headquartered in London.
What Makes Dailoqa Different From a Traditional AI Company?
A traditional or general-purpose AI vendor typically builds one product and adapts it across industries afterwards. We build exclusively for financial services, which changes the starting point for every design decision.
Dimension | Traditional or general-purpose AI vendor | Dailoqa |
Industry focus | Multiple industries, adapted after launch | Financial services exclusively, from the start |
Architecture starting point | General capability, compliance added later | Compliance and audit requirements built in from the start |
Human oversight design | Often a generic review step | Role-specific maker-checker separation by design |
Underlying philosophy | AI replaces or automates a task | Combined Intelligence, agentic AI and human judgment working together |
Our exclusive financial services focus means compliance, audit and human oversight are architectural decisions for us, not features added later.
Meet the Team Behind Dailoqa
Dailoqa is built by a team with deep roots in global financial services and enterprise AI engineering, including former CIOs, business heads of global banks, and senior partners from top consulting and technology firms. Our team spans over 200 practitioners across AI and financial services.
Our Financial Services Experts
Dr PG Raghuraman, Advisor. A strategy and business consultant with over 37 years of experience across FMCG, engineering, textiles, chemicals and airlines, including setting up BPO delivery centres for Accenture in India. He holds a doctorate in Leadership and Psychological Resilience from IIM Lucknow.
Sonali Kulkarni, Partner. Leads Dailoqa's Industry Propositions and Consulting team globally as the company scales Broccoli™ across India, the Middle East, the UK, Australia, ASEAN, Africa and Switzerland. She joined from Microsoft, where she was BFSI Country Head for India and South Asia, with prior roles at Accenture, EY and GE Capital. With more than two decades in BFSI, she has worked with financial institutions through core digitisation, operating model modernisation, cloud adoption, intelligent automation and now enterprise AI.
Alex Vanderlip, Advisor. A management consultant and former investment banker with experience across consulting and financial services, and co-founder of an EdTech start-up. He now focuses on advisory and board roles, particularly with businesses undergoing transformation or scaling rapidly.
Lupo von Maltzahn, Advisor. Brings experience in financial analysis, business transformation and go-to-market strategy across wealth and asset management, investment banking and corporate banking. He was Managing Director in Accenture's Global Banking Strategy Practice and has chaired Three Body Capital for over six years.
Sunil Srivastava, Partner. Spent nearly 45 years in Indian banking and finance, most of it at the State Bank of India, where he served as Deputy Managing Director. In his final role, he led corporate banking for large corporate clients; before that, as Deputy Managing Director for Corporate Strategy and Digital Businesses, he drove SBI's entry into digital financial services, including wealth management, e-wallets, mobile banking and fintech partnerships. He now serves as an Independent Director on several company boards and as Senior Advisor to the World Bank's Energy and Extractives programme in India.
Ajay Agarwal, Partner. Brings three decades of experience in Corporate and Investment Banking, Corporate Risk Management and Finance Risk Management, with senior roles at Citibank, JPMorgan and Wells Fargo across the US and UK. His expertise spans credit, market and counterparty, model, liquidity, interest rate and capital adequacy risk. At Dailoqa, he focuses on ensuring agentic AI deployments meet the rigour and governance financial services regulation demands.
Alan Thomas, Partner. A financial services professional with global experience across wealth and investment banking, including senior roles at Merrill Lynch and Credit Suisse, where he served as Global Head of FX Structured Sales and led the third-party bank sales team for FICC. Over the past 12 years, he has worked as a subject matter expert for a Big Four consultancy, developing innovation playbooks, commercialisation strategies and scale-up programmes for fintechs.
Ian Cooke, Partner. A financial services and capital markets specialist with experience across investment banking, asset management and wealth management at Tier 1 institutions. He has held senior trading and sales roles, and in recent Big Four consulting work has advised investment and wealth clients on carbon markets, digital personalisation, fintech and applied AI.
Graeme King, Partner. Spent over three decades at the highest levels of global finance, including Managing Director roles at Bank of America Merrill Lynch and RBC Capital Markets, where he led a team managing over $1 trillion in annual turnover. He spent the last eight years as CEO of The Corellian Academy. At Dailoqa, he connects agentic AI capabilities with asset management and advisory. “I have always believed that the strongest teams are built through collaboration and efficient, innovative processes,” Graeme says. “Joining Dailoqa is an opportunity to bring that same discipline to the next frontier of finance, that is, AI.”
Matt Jarman, Partner. A financial services consulting professional with deep expertise in risk, regulation and technology, including a key role in the inception of the FICC Markets Standards Board. He works across regulatory bodies, standards setters and client stakeholders to embed new technologies into operating models.
Bashar Kilani, Partner. Brings nearly 30 years of global experience, with senior leadership roles at Accenture and IBM. He helps organisations embrace AI to create economic value through leadership and culture, accelerated digitisation and responsible AI practices, and is a regular media commentator on digital economy trends.
Our Technology & AI Leadership
Shuki Idan, Partner. Based in Bangkok, Shuki is a Data and AI leader with over three decades of experience, having pioneered work in neural networks and machine learning since the early 1990s. With roots in Israel's innovation ecosystem, he holds multiple patents and has helped global enterprises and financial institutions translate AI technologies into measurable outcomes. At Dailoqa, he focuses on helping clients move from experimentation to production-scale impact.
SP Motwani, Partner. Brings three decades of experience leading large-scale digital, data and cloud transformations for Fortune 500 companies. During 24 years at Accenture, he played a role in growing its Advanced Technology Centers in India from a small team to over 300,000 professionals, and most recently led Generative AI and Agentic AI Technology Activation for Accenture across North America. At Dailoqa, he focuses on strategic scaling and disciplined execution of agentic AI deployments.
Joel Miller, Partner. Co-founder of ExoBrain, an AI-native consultancy, with over two decades of experience across Accenture, Deloitte, Janus Henderson and Schroders. He led Deloitte Ventures' risk and regtech product team and developed AI-driven security solutions at Accenture using digital twins, risk quantification and cyber mesh technologies.
Joost de Jonge, Partner. Co-founder of ExoBrain, with leadership roles at Accenture, Schroders and BlackRock. As Head of Innovation at Schroders, he led global initiatives to increase agility across the 150-year-old firm. At Dailoqa, he focuses on helping clients realise AI's value responsibly, with an emphasis on reshaping the future of work.
Ian Lloyd, Partner. Brings over 20 years of experience in digital and data transformation, spanning big data analytics, AI, cloud technologies and machine learning. He has led cross-functional teams on data infrastructure, governance and regulatory compliance, including managing key Transitional Services Agreements during the separation of TSB from Lloyds.
How Does Dailoqa Approach Responsible AI?
We build Responsible AI around three principles that apply to every agent in a workflow: secure-by-design architecture, compliance-first policy enforcement, and explainability that lets a person or an auditor see why an agent reached a given output.
All agents function within a well-defined scope. High-impact actions, payments, lending decisions, and changes to accounts require a check before they take effect. Every action an agent takes is recorded in a way that allows the situation to be reconstructed afterwards, which matters for institutions that must comply with frameworks such as the EU AI Act's requirements on human oversight and record-keeping.
We build secure-by-design architecture, compliance-first policy enforcement and explainability into every agent. Responsible AI is how we build, not just a value we state.
From AI Adoption to AI-Native Financial Services
Most financial institutions have already been through a first wave of AI adoption, chatbots, copilots, and generative AI tools added on top of existing systems. That wave delivered real value for single-output tasks such as drafting and summarising, but it left the multi-step, judgment-heavy parts of a workflow largely untouched.
The next phase is AI-native financial services. Rather than incorporating AI features into existing software, the workflow is designed around what agentic AI can coordinate and what a person needs to review. We think this change matters more than any single model upgrade, since it determines which decisions an institution can scale and which it chooses to keep with a person.
AI-native financial services means designing the workflow around agentic AI and human oversight from the start, rather than adding AI on top of existing systems.
Conclusion
We build agentic AI exclusively for financial services, with compliance, audit and human oversight designed into the architecture rather than added afterwards. The enterprise-grade Broccoli™ platform is the technology layer behind our approach, applied across retail banking, wealth management, capital markets and beyond, in markets from the UK to Australia.
This is the vision our founders set out to build in 2024, and it is the same one guiding every workflow we ship today.
Frequently Asked Questions About Dailoqa
What problems does Dailoqa's Agentic AI solve for financial institutions?
We address workflows that combine structured data, unstructured documents and judgment-based decisions, such as onboarding, credit assessment, transaction investigation and claims processing, where legacy automation historically stopped at the structured parts of the process.
How can Dailoqa help banks adopt Agentic AI?
We work with banks to map which parts of a workflow suit agentic AI and which decisions should stay human, then apply our enterprise-grade Broccoli™ platform to that workflow with role-specific agent policies and audit logging built in from the start.
What makes an AI-native approach different from traditional AI implementation?
A traditional implementation adds AI features to existing software after the fact. An AI-native approach designs the workflow, including agent roles, oversight points and audit requirements, around agentic AI from the beginning.
Can Dailoqa's Agentic AI be used for regulated financial services workflows?
Yes. We build our systems specifically for regulated financial services, with role-specific agent permissions, maker-checker separation for high-impact actions, and immutable audit trails designed to support regulatory and audit review.
What types of banking workflows can Agentic AI automate?
Multi-step, judgment-adjacent workflows such as onboarding, KYC review, credit memo preparation, transaction investigation and trade reconciliation, where different parts of the process require different expertise and different levels of oversight.
How does Broccoli™ support enterprise Agentic AI adoption?
Broccoli™ provides the orchestration layer that scopes each agent to a specific role, enforces maker-checker separation on high-impact actions, and logs every agent action for audit and compliance purposes.
How does Dailoqa combine AI with human expertise?
Through Combined Intelligence, our operating principle where agentic AI runs the process and coordination across a workflow while people retain ownership of decisions involving risk, suitability or regulatory judgment.
Is Dailoqa suitable for enterprises starting their Agentic AI journey?
Yes. We work with institutions at different stages of agentic AI adoption, from initial workflow mapping through to full production deployment, across the markets we operate in.
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