Intelligent intake & classification
Emails, forms, and documents parsed into structured cases with confidence scores routing to straight-through or review paths.
AI Automation
Intelligent workflows and process automation for enterprise systems.
Intelligent workflows, process automation, and AI integrated with ERP, CRM, and business systems, with confidence routing, exception handling, and cost discipline.
Capabilities
Automation surfaces we industrialize
We target workflows where manual handoffs create latency, inconsistency, or compliance exposure, not tasks that merely look automatable in a demo.
Dynamic routing & prioritization
Queue logic that weighs SLA, skill match, risk tier, and backlog state, adjustable by operations leadership.
Document generation & reconciliation
Draft contracts, summaries, and reconciliation memos sourced from system-of-record data with citation back to fields.
Exception orchestration
When automation stalls, cases land in specialist queues with full context, suggested next actions, and audit history.
Perspective
Automation that respects the backbone systems
Enterprise automation fails when AI sits outside the transactional core, creating shadow processes that diverge from ERP truth or bypass approval hierarchies.
InheritX designs automation fabric that reads and writes through governed integration points: event streams, approved APIs, and idempotent job patterns your integration team can support.
Intelligence augments deterministic steps, classification, extraction, summarization, while critical financial and policy commits remain under existing controls unless you explicitly expand autonomy.
Dual view
Where AI adds leverage in workflows
Deterministic backbone
Transaction posting and ledger updates
Identity, authorization, and segregation of duties
Scheduled batch jobs with fixed business rules
AI-accelerated layers
- Unstructured document understanding
- Natural-language case summarization for reviewers
- Anomaly surfacing before hard-rule triggers fire
- Adaptive routing when backlog or risk profile shifts
How we engage
Automation rollout model
01
Process instrumentation
Baseline cycle times, error rates, and rework drivers on the target workflow before introducing AI steps.
02
Integration mapping
Document source and sink systems, rate limits, and failure semantics for each touchpoint in the flow.
03
Shadow mode
Run AI suggestions alongside human decisions; measure agreement and catch systematic extraction gaps.
04
Controlled auto-path
Enable straight-through processing only for cases above confidence and policy thresholds.
05
Continuous improvement
Sample production outcomes, refresh training data, and tune routing as volume and edge cases grow.
Integrated
ERP, CRM, ITSM, custom APIs
Measured
KPIs tied to workflow SLAs
Resilient
Graceful degradation to manual queues
Auditable
Decision rationale retained per case
Continue
Related solutions
FAQ
AI Automation FAQ
Usually no, we extend orchestration you already operate, adding AI steps where unstructured data or judgment-heavy prep work slows the flow.
Confidence monitoring, periodic human audits on auto-processed cases, and alerts when extraction fields fall below agreed thresholds.
Yes, with classification-aware handling, retained evidence, and human approval on commits that touch compliance boundaries.
Next step
Map this capability to your mandate.
A focused strategy conversation, constraints, systems, and what production readiness looks like for your organization.