Detect
Receive the failed-payment event and correlate the customer, channel, transaction and permitted operational signals.
Jai for Business · MSMEs and Solutions Partners
Build conversational AI around the context of real work.
Jai for Business is a multimodal, context-driven platform architecture for designing and implementing AI cognition pathfinder use cases. Growing businesses and Solutions Partners can begin with one measurable operational objective, integrate it into current technology and processes, and evolve it under governed human control.
Customer signalContextDecisionFulfilmentLearning loop
Banking example
Failed payments pathfinder, integrated into the platforms people already use.
A failed payment is rarely just an error code. The pathfinder connects the customer, channel, payment state, merchant, policy and available remedies so an approved agent can explain what happened, attempt a governed resolution or hand the case to a person with useful context.
Understand
Bootstrap bounded context from the CKB, current process state and authorised customer history.
Resolve
Select controlled tools for retry, an alternative payment path, guidance, investigation or human review.
Fulfil
Complete the approved action across chat, voice or an existing business workflow and record the outcome.
Learn safely
Evaluate the objective, observe exceptions and improve the governed pattern without silently changing production authority.
Modular platform architecture
Compose the cognition path. Keep every boundary visible.
Each module has a bounded responsibility, evidence surface and human owner. MDBC maps the modules into the organisation’s departments, roles, controls, documents and live workflows.
Multimodal
Bring together approved text, documents, images, structured events and audio without treating every source as equally authoritative.
Customer Agents
Provide role-bounded conversational agents for customers, staff and partners with clear identity and escalation rules.
Context AI
Assemble the smallest useful context from session state, business events, policy and authorised knowledge.
Voice Channel
Support spoken interaction with consent, identity, transcription quality, confirmation and human-assistance controls.
Orchestration
Route intents, agents, models, tools and process steps through explicit objectives, policies and stopping conditions.
Fulfilment
Carry an approved decision into an existing system or workflow and return verifiable completion or failure evidence.
Skills
Package reusable business capabilities with inputs, permissions, expected outputs, tests and accountable ownership.
Context Knowledge Base (CKB)
Govern the operational facts, policies, provenance, freshness, retrieval scope and lifecycle used for grounding.
Loop-back
Combine evaluation, observability and Agent-to-Human Handoff so failures become controlled learning signals.
MDBC
Connect the cognition path to departments, responsibilities, controls, information assets and cross-team processes.
Reusable Jai AI patterns
Start with patterns that make safe delivery repeatable.
Context Bootstrap
Establish identity, objective, authority, current state and the minimum grounded context before cognition begins.
Controlled Tools Use
Allow only named tools, bounded arguments, policy checks, receipts and reversible actions where possible.
Failed-Objective Resolution
Recognise when the requested outcome was not achieved, explain why and choose retry, alternative or escalation.
Omnichannel Continuity
Carry an authorised objective and context across chat, web, desktop and voice without losing correlation.
Human Handoff
Transfer the case, context, attempted actions, evidence and unresolved decision to an accountable person.
Voice Assurance
Confirm critical spoken inputs and actions, measure transcription uncertainty and provide a safe human route.
CKB Governance
Control knowledge ownership, provenance, approval, freshness, retrieval boundaries, correction and retirement.
Agent Release Assurance
Require scenario tests, security controls, evaluation thresholds, approval evidence, rollback and monitored release.
Pathfinder delivery
Prove one cognition path before scaling the platform.
- Frame the objective.Define the customer or operational outcome, baseline, authority and measurable acceptance criteria.
- Map the current process in MDBC.Identify people, systems, policies, information, exceptions and handoff points before adding AI.
- Compose and integrate.Select the required modules and patterns, then connect them through controlled interfaces to current platforms.
- Evaluate with humans.Test normal, adverse, ambiguous and attack cases with operational owners and representative users.
- Release with observability.Approve a bounded production scope, monitor outcomes, preserve rollback and expand only from evidence.
Business assurance: a pathfinder is not a claim of guaranteed automation or financial outcome. Production use requires organisation-specific security, privacy, legal, operational and human validation.
Build with Jai AI