Advisory
Use-case discovery, architecture and platform selection, AI governance design and business cases for leadership and risk committees.
- Discovery sprint
- AI strategy
- Governance
AI engineering for financial services
AI agents for banks, insurers and fintechs.
We design, build and run governed AI agents for KYC, claims, AML and customer operations. They work inside your AWS, Azure or Google Cloud, are powered by Claude, and a person approves every decision that matters.
Builds on Claude · AWS · Azure · Google Cloud
Trusted by product and engineering teams at
Platforms we build on
Engineered on the platforms financial institutions already run.
Your agents should run where your data, identity and controls already are. We engineer natively on each hyperscaler, and use Claude through whichever route your cloud and procurement teams prefer.
Claude
Claude-powered agents, copilots and document intelligence, delivered through the Claude API, Amazon Bedrock, Google Vertex AI or Microsoft Foundry.
- Claude API
- Agent SDK
- MCP
- Claude Code
Amazon Web Services
Agentic workloads on Amazon Bedrock and Bedrock AgentCore, with serverless integration and landing zones designed for regulated workloads.
- Bedrock
- AgentCore
- SageMaker
- Lambda
Microsoft Azure
Copilots and agents on Microsoft Foundry, wired into Microsoft 365, Teams and Fabric, using Entra ID for identity and Purview for governance.
- Foundry
- Azure OpenAI
- Fabric
- Copilot Studio
Google Cloud
Agents on Vertex AI with Gemini or Claude, grounded in BigQuery and Cloud Storage, inside VPC Service Controls.
- Vertex AI
- Gemini
- BigQuery
- Agent Builder
Claude and Anthropic are trademarks of Anthropic, PBC. AWS and Amazon Bedrock are trademarks of Amazon.com, Inc. Microsoft, Azure and Foundry are trademarks of Microsoft Corporation. Google Cloud, Vertex AI and Gemini are trademarks of Google LLC. Logos identify the technologies we build on. Skugal is an independent services firm and is not affiliated with or endorsed by these companies.
An agent at work
The agent does the legwork. Your analyst makes the call.
Here, an AML investigation agent built on Claude pulls context from core banking, sanctions lists and the transaction warehouse through scoped tools, then drafts a cited case narrative. Nothing is filed until a named analyst approves it.
- Read-only, least-privilege tools exposed through MCP
- Every retrieval and tool call logged for audit and replay
- Maker–checker approval before anything is filed
How we serve clients
Advise. Build. Run.
We’re a services firm, not a product vendor. Clients bring us in to shape their AI strategy, deliver production systems, or operate them long term, on whichever cloud and model fits.
Implementation
Production agents, copilots and RAG systems on Claude, AWS, Azure or Google Cloud, integrated with your systems and delivered with evals.
- Agents
- Copilots
- RAG
- Integrations
Managed services
AgentOps after go-live: monitoring, eval regression, cost optimisation, model upgrades and new workflows under SLA.
- AgentOps
- SLA support
- Optimisation
Markets & industries
Where we deliver Claude.
We implement Claude-powered solutions for enterprise clients, led from North America and delivered across Europe and Asia, with financial services as our deepest specialism.
Markets
Primary marketNorth America
Also serving
- Europe
- India
- Asia-Pacific
- Japan
- Korea
Industries
Primary focusFinancial Services
Also serving
How we work with Claude
PrimaryClaude-powered solutions for enterprises
Also
- Advisory, technical and managed services around Claude
- Cloud platform integration on Amazon Bedrock and Google Vertex AI
- Applications built on the Claude API
Financial services use cases
Where agents earn their place in FSI.
We start with high-volume, document-heavy workflows that follow clear rules, where an agent can do the legwork and a person keeps the decision.
Banking
Speed up onboarding, lending and servicing without loosening the controls your regulators expect.
Banking practiceKYC & onboarding agent
Collects and reads identity and entity documents, screens parties and assembles a complete case for analyst review.
- Document AI
- Screening
- Case mgmt
Credit memo copilot
Drafts credit memos from financial statements, bureau data and lending policy, then flags exceptions for the underwriter.
- Spreading
- Policy RAG
- Citations
Disputes & chargebacks
Classifies disputes, gathers transaction evidence and drafts responses within card-scheme timelines.
- Card systems
- Evidence packs
- SLA tracking
Contact-centre copilot
Gives agents answers grounded in product and policy documents, writes after-call summaries and suggests the next best action.
- Grounded answers
- Summaries
- QA scoring
Insurance
Shorten the time from first notice to decision, and from broker submission to quote.
Insurance practiceFNOL & claims intake
Captures first notice of loss from any channel, extracts the facts, checks coverage and routes the claim to the right handler.
- Omnichannel
- Coverage check
- Triage
Submission ingestion
Turns broker emails, statements of values and loss runs into structured, appetite-checked submissions.
- Email parsing
- SOV extraction
- Appetite rules
Policy servicing agent
Handles endorsements, certificates and mid-term changes against the policy admin system, with approval gates.
- Policy admin
- Approvals
- Audit trail
Leakage & fraud triage
Spots fraud signals, subrogation opportunities and missed recoveries, then explains its reasoning to investigators.
- Signals
- Explanations
- SIU handoff
Capital Markets & Wealth
Give research, operations and advisory teams back the hours they spend gathering information.
Capital markets practiceResearch copilot
Searches filings, transcripts and internal notes together, and gives answers with source citations an analyst can check.
- Filings
- Transcripts
- Entitlements
Trade-ops break resolution
Investigates reconciliation breaks across systems, proposes fixes and drafts counterparty messages.
- Reconciliation
- OMS / PMS
- Exceptions
Advisor meeting prep
Prepares client briefs, portfolio commentary and follow-ups from CRM, holdings and market data.
- CRM
- Holdings
- Commentary
Mandate & suitability checks
Checks proposed trades and recommendations against mandates, restrictions and suitability rules before they are executed.
- Pre-trade
- Rules engine
- Evidence
Risk & Compliance
Let investigators and compliance officers spend their time on judgment, not evidence gathering.
Risk & compliance practiceAML alert investigation
Gathers KYC, transaction and adverse-media context for each alert, then drafts the disposition and case narrative.
- TM alerts
- Adverse media
- SAR drafting
Regulatory change mapping
Reads new circulars and rules, maps them to your policies and controls, and drafts the impact assessment.
- Obligations
- Control mapping
- Gap analysis
Communications surveillance
Cuts down false positives by putting flagged chats and emails in context before they reach a reviewer.
- Lexicon + LLM
- Context
- Escalation
Model risk documentation
Generates and maintains model documentation, validation evidence and change logs for every AI system you run.
- Model cards
- Validation
- Change logs
Governed by design
Autonomy where it’s safe. Control where it counts.
Financial services can’t run on demos. Every agent we ship comes with the controls your CISO, compliance and model-risk teams will ask about, built in from day one.
Human-in-the-loop
Any action that moves money, changes a record of truth or contacts a customer needs an explicit approval step.
Least-privilege tools
Each agent gets scoped tool permissions through MCP servers and API gateways, with no standing access to production systems.
Every step on the record
Prompts, retrievals, tool calls and approvals are logged so auditors can replay any decision.
Evaluated continuously
Golden datasets, red-team suites and regression gates run in CI, with quality and drift monitored in production.
Your cloud, your boundary
Agents deploy in your own AWS, Azure or Google Cloud tenancy, with private networking, customer-managed keys and data residency controls.
Model-risk ready
Model cards, validation evidence and change logs are structured for model risk management reviews.
Reference architecture
How an FSI agent is actually built.
The same blueprint works on all three clouds. The agent runtime plans and acts, tools are exposed through governed interfaces, and a control layer wraps everything.
Channels
Ops workbenchCase and queue UIs
Contact centreVoice and chat
Teams · SlackEmployee copilots
APIs & eventsStraight-through flows
Agent runtime
Orchestrator agentClaude via Bedrock, Vertex AI or Foundry. Plans, delegates to specialist sub-agents, manages memory and asks for approval when needed.
Specialist agentsExtraction · Screening · Drafting
Governed tools
MCP serversScoped, versioned tools
API gatewayRate limits and policies
ApprovalsMaker–checker queues
Systems & data
Core banking · Policy adminSystems of record
CRM · Case managementCustomer context
Lakehouse · Vector storeEntitlement-aware retrieval
Market & reference dataLicensed feeds
Guardrails & PII redaction
Identity & entitlements
Observability & evals
Audit log & replay
How we engage
From one workflow to an agent program.
We prove value on a single workflow first, then turn what works into a repeatable platform your teams own.
Discover
Typically 2 weeksScore candidate workflows on value, risk and data readiness, and agree success metrics with the business and risk teams.
Governed pilot
Typically 6–8 weeksShip one workflow end to end in your cloud, with evals, human review and real users.
Production
Typically 8–12 weeksHarden, integrate, pass security review and produce model-risk documentation.
Run & scale
OngoingAgentOps covering monitoring, cost control and eval regression, then reuse the platform for the next workflows.
Quality you can audit
ISO 9001:2015 certified delivery.
Our quality management system has been independently assessed and certified for providing IT services and software development solutions. In practice, that means documented processes, quality gates and annual third-party surveillance audits behind every engagement.
- Certificate
- QD-98140/1125
- Issued
- 24 Nov 2025
- Valid until
- 23 Nov 2028
- Documented delivery lifecycle with quality gates at design, build and release
- Engagements run inside client cloud tenancies, under NDA and least-privilege access
- Security, evaluation and model-risk artefacts delivered as standard
Trust pillars
Why clients and platforms trust Skugal.
These are the questions enterprise buyers and cloud and model providers ask of any services firm they work with. Here is how we answer them.
Quality management
ISO 9001:2015 certified delivery with documented quality gates.
Information security
Least-privilege access, client-tenant delivery and a secure SDLC.
Data protection
Your data stays in your cloud and is never used to train models.
Responsible AI
Human approval, evals, red-teaming and model-risk documentation.
Platform depth
Native engineering on Claude, AWS, Azure and Google Cloud.
Proven delivery
$300K+ delivered, 100% Job Success Score, Top Rated on Upwork.
Transparent engagements
Fixed-scope pilots, named owners and written acceptance criteria.
No lock-in
Code, runbooks and repositories live in your accounts from day one.
Track record
Trusted by the teams who build on these platforms.
From an AWS Bedrock Agents engineer to AI-native startups, clients rate our work highly. Every review below is verified on Upwork.
$0K+Delivered on Upwork
0%Job Success Score
Top RatedUpwork talent badge
0K+Engineering hours delivered
He joined our team at a critical time and demonstrated a rare blend of technical excellence, strategic thinking, and ownership well beyond expectations.
He has got great handle over AI agent development and I highly recommend him for building projects around AI agents.
He did not only help with implementation, but also understood the goal after our first discussion and designed a solution draft very quickly.
Insights
Field notes for AI leaders in financial services.
Research and playbooks from teams who ship agents to production.
Research462 YC startups: where AI is going nextWe studied every YC-funded company in 2026 and found six bets that are reshaping enterprise software.Read the research
GuideEnterprise AI security guideTool permissions, PII handling, audit trails and human-in-the-loop patterns for regulated environments.Read the guide
PlaybookProduction RAG, done properlyChunking, metadata, hybrid search and entitlement-aware retrieval for policy and research corpora.Read the playbook
Can our data stay inside our own cloud?
Yes. We deploy agents into your AWS, Azure or Google Cloud tenancy and reach models through your cloud provider: Claude on Amazon Bedrock, Google Vertex AI or Microsoft Foundry. Private networking, customer-managed keys and region pinning are part of our standard landing zone.
How do you keep agents safe in regulated workflows?
Agents get scoped tools rather than broad system access. Consequential actions require human approval, and every step is logged for replay. We run evaluation and red-team suites before launch and on every change, and deliver documentation your model-risk function can review.
Which models do you use?
We’re model-agnostic but opinionated. For reasoning-heavy, long-document and agentic work we often lead with Claude. We also use GPT, Gemini and open-weight models where they fit, and choose per task based on evals, latency and cost.
How do you work with AWS, Microsoft, Google and Anthropic?
We build natively on all four platforms and align our reference architectures with each provider’s recommended patterns. Our platform pages describe how we deliver on each one, and we can work with your own cloud and model account teams on architecture reviews.
How does an engagement start?
Usually with a two-week discovery. We pick one workflow, map the data and controls, and agree success metrics. That becomes a fixed-scope governed pilot in your environment.
Is Skugal certified?
Yes. Skugal Technologies Private Limited holds ISO 9001:2015 certification (certificate QD-98140/1125, valid to November 2028) for providing IT services and software development solutions. See details.
Start with one workflow
Bring us a workflow. We’ll show you the agent.
A 45-minute working session with an AI architect. Bring a process, and leave with an architecture sketch, a risk view and a plan for a pilot.