Connect what you have
Bring ERP exports, spreadsheets, and documents into one governed foundation.
See selected workAI agents that
AI agents that
run your enterprise.
Better decisions.
Happier customers.
Better decisionsHappier customersTraceable outcomes
Systems in motionIllustrative workflow
ERP records
Stock sheets
Quality reports
Governed
doubtbuddy.aiDispatch agent
3 stages
Operational review
Decision preparedDispatch plan
ConnectGovernAnswer · recommend · act
Built around the systems you already run
Keep your tools.
Put them to work together.
A governed agent connects the systems your teams already know to actions they can review.
Office & collaboration
Excel
Word
Google Docs
Google Sheets
Teams
Slack
Business systems
SAP
Salesforce
HubSpot
Zoho CRM
Odoo
Finance & commerce
TallyPrime
Zoho Books
Razorpay
Shopify
Knowledge & work
Google Drive
SharePoint
Confluence
Notion
Jira
Asana
ClickUp
Data & compute
Snowflake
AWS
Google Cloud
NVIDIA
Governed datadoubtbuddy.ai
agent system
Answer with sourcesRecommend next stepsAct with approval
Is this your team?
A familiar problem.
A clearer next move.
From scattered records to the next decision.
Explore operationsAct on exceptions
Prepare stock, quality, and dispatch decisions with supporting records.
Useful AI. Within your boundaries.
Explore private AIChoose your infrastructure
Cloud, private cloud, or on-premise GPUs.
Keep control of access
Enforce permissions at the data layer and trace answers to their sources.
Build it. Take it over. Move it forward.
Explore product engineeringStart from the real codebase
Build a new product or assess and extend an existing system.
Define what ships
Deliver against written milestones, with hypercare after launch.
More execution. Clear approval gates.
Explore growth workflowsTurn research into work
Connect market research, campaigns, and customer responses.
Keep the team in control
Review consequential actions before they reach your customers.
What we build
Four ways to put
AI to work.
Operations & decisions
From records to decisions.
Reporting, exceptions, and decisions backed by operational data.
Explore the workPrivate enterprise AI
Intelligence, kept in-house.
Source-linked answers from company knowledge. Within your infrastructure.
Explore the workMarketing & commerce
Ideas into execution.
Research, campaigns, and customer responses—with approval controls.
Explore the workAI-native product engineering
Built to ship. Built to stay.
Build a new product. Take over an existing one.
Explore the workBuilt for production
Trust, built into
every layer.
Reliability is part of the architecture and the delivery contract.
- 01
Validated data
Incomplete inputs and data gaps stay visible.
- 02
Encoded rules
Business logic is explicit, testable, and reviewable.
- 03
Structural access
Permissions are enforced at the data layer.
- 04
Traceable outputs
Answers point back to the records used.
- 05
Written acceptance
Milestone sign-off, followed by hypercare.
Data foundationBusiness controlsAccepted in production
Selected work.
Commerce
Couture commerce
Marketing and commerce workflows that give a lean luxury brand more execution capacity.
Initial phases live; expansion proposedView case studyCommerce
Proof, with context
Real work.
Clear status.
Numbers, delivery stages, and client feedback are published only when they can be supported.
Operations
How an operations team is connecting years of scattered records
Delivery stageIn deliveryDeploymentCloud or private
Read story Commerce
How a lean commerce team is expanding its execution capacity
Delivery stageInitial phases liveDeploymentControlled cloud
Read story Approved client feedback will appear here with the project and delivery context.
Client review · awaiting approvalVerified figures will include baseline, period, and evidence.
How we work with clients
From first workflow
to production.
Clear scope. Visible checkpoints.
Support after launch.
- 01Align
Frame the workflow
Map the systems, owners, constraints, and first useful outcome.
- 02Define
Write acceptance criteria
Agree what working means before engineering begins.
- 03Build
Build in milestones
Review working software and real integrations at each checkpoint.
- 04Prove
Validate with real data
Test rules, permissions, evidence, and edge cases together.
- 05Operate
Deploy and hypercare
Launch on your infrastructure and stay through early production.
Deployment, on your terms
Your cloud.
Your GPUs. Your choice.
Example environments
AWSAzureGoogle CloudNVIDIA
Our products
Built from real
operating problems.
We build products too. That keeps our product judgment grounded in shipping, ownership, and daily use.
The people behind the work
We’re builders.
We started that way.
Our first product helped students solve doubts. Acquired by AppX. Today, we build enterprise AI systems.
Before we talk
Questions, answered.
Can this run fully on our own servers?
Yes, when the use case and infrastructure support it. We can design private cloud, on-premise, or air-gapped architectures where external AI services are excluded by design.
How do you reduce unsupported AI answers?
We validate source data, encode business rules, show the records used, and make missing data visible. The exact controls are agreed around the workflow.
We have legacy systems with no APIs. Can you connect them?
We start with a system inventory and choose a practical integration path: read-only connectors, exports, change-data-capture, or a staged replacement where appropriate.
How long until we see something working?
Milestones depend on scope, data access, and the systems involved. We agree the first useful milestone and its acceptance criteria before delivery begins.
How do you structure engagements?
We work against written milestones and acceptance criteria. The written agreement sets out ownership, access, and handover, with support continuing after go-live when agreed.
Who owns the code and data?
Ownership of project-specific deliverables, code, data, and documentation is set out in the written agreement. Handover materials and support are agreed as part of the scope.
What happens after launch?
We provide hypercare around milestones and can continue with a monthly enhancement or maintenance engagement when that is useful.
Start with one workflow