Custom agentic workflows for industry

From enterprise datato AI-driven execution

TELEMETRY

sensor streams

DOCUMENTS

forms · records

SYSTEM EVENTS

APIs · webhooks

DATABASES

records · logs

Orchestration
Plannerdecompose
Routerdispatch
Memorystate · vectors
RetrievalRAG · tools

MedAgent

Healthcare

ChipSense

Semiconductor

MaintainAI

Maintenance

FlowAgent

Automation

DocuMind

Documents

We design, build, and deploy bespoke multi-agent systems — engineered for your industry, data, and workflows.

No commitment · Response within 24 hours

OUTCOME

Faster cycle time across core operational workflows

20–40%

OUTCOME

Less manual effort on repetitive, rules-based work

25–50%

TIMELINE

From pilot to first production deployment

8–16 wks

Engineered to enterprise governance standards

EU AI Act
HIPAA
SOC 2
GDPR
Human-in-the-loop
Audit trails
Data residency
On-premise ready
01What We Do

AI consultation built for operational execution

From first assessment to pilot launch, we run a structured AI program focused on measurable business outcomes.

01

Diagnose Bottlenecks

We map where cycle time, handoffs, and manual work are constraining delivery and margin.

Output: bottleneck map + KPI baseline
02

Design Agent Workflows

We define agent roles, escalation paths, and system touchpoints tailored to your operating model.

Output: architecture and rollout blueprint
03

Deploy for Impact

We launch pilots with governance, quality controls, and clear ownership to reach production safely.

Output: tracked gains in speed, quality, and cost
02Problem → Agent → Outcome

Where AI agents create immediate lift

The bottleneck, the agent intervention, and the impact you can expect.

01
Bottleneck

Multi-team handoffs create delays and missed follow-through.

Agent intervention

Coordination agents route tasks, approvals, and escalations across systems.

20–40%

faster process cycle times

02
Bottleneck

Inconsistent decisions across teams increase rework and exceptions.

Agent intervention

Policy-aware agents apply rules consistently and surface edge cases early.

15–35%

fewer operational errors

03
Bottleneck

High manual effort in repetitive workflows limits team capacity.

Agent intervention

Task automation agents handle repetitive steps while humans manage exceptions.

25–50%

less manual processing effort

03Methodology

How we deploy AI in operations

A practical four-phase model that moves from diagnosis to measurable production impact.

01

Diagnose

Map workflows, constraints, and baseline KPIs to identify highest-value opportunities.

Deliverable — Operational Readiness & Opportunity Map

02

Design

Define agent roles, escalation logic, data pathways, and governance controls.

Deliverable — Agent Blueprint & Pilot Scope

03

Deploy

Launch pilots with integration, QA, and enablement for frontline and leadership teams.

Deliverable — Go-Live Plan with Measurable Milestones

04

Optimize

Track performance, reduce costs, and improve quality through ongoing tuning cycles.

Deliverable — KPI Dashboard and Optimization Backlog

04Services

Full-lifecycle consulting & implementation

From strategic assessment to production optimization, we support every stage of AI agent adoption.

01 / 06

Agent Strategy & Consulting

Assess AI readiness and map high-impact agent opportunities aligned to operational goals.

ROI MappingReadinessPrioritization
02 / 06

Multi-Agent Architecture

Design resilient agent topologies that coordinate, delegate, and scale across systems.

System DesignOrchestrationScale
03 / 06

Custom Agent Development

Build production-grade agents with reasoning, tool use, and memory for real workflows.

LLM IntegrationToolsMemory
04 / 06

Enterprise Integration

Embed agents into CRM, ERP, and data platforms with secure and low-friction rollouts.

CRMERPAPI
05 / 06

Monitoring & Optimization

Track latency, cost, and quality with dashboards and continuous improvement loops.

PerformanceCostA/B Testing
06 / 06

Security & Compliance

Harden agent pipelines against prompt injection, leakage, and compliance risk.

EU AI ActHIPAASOC2
07Representative Voices

What operations leaders tell us

Representative composites of the outcomes and concerns we hear from operations and technology leaders — not named clients.

▸ REPRESENTATIVE
We'd run two agent pilots that never reached production. The discipline around integration, evaluation, and governance is what finally got a workflow live and measured.
OP

VP of Operations

Industrial manufacturing, Representative composite

▸ REPRESENTATIVE
They treated our constraints — data residency, audit trails, human-in-the-loop review — as first-class design requirements, not afterthoughts.
MD

Chief Medical Officer

Regional health system, Representative composite

▸ REPRESENTATIVE
The value wasn't a flashy demo. It was a documented architecture, a tracked KPI baseline, and a rollout plan our team could actually own.
PE

Head of Process Excellence

Financial services, Representative composite

08Get Started

Get a practical AI operations roadmap

Start with a focused strategy session. We map priorities, define pilot scope, and outline a realistic timeline for measurable impact.

  • A mapped view of your highest-value bottlenecks
  • A pilot scope with timeline and success metrics
  • A clear build-or-buy recommendation

No commitment · Response within 24 hours

▸ WEEKLY INTELLIGENCE BRIEF

Practical deployment patterns, benchmarks, and governance notes for enterprise leadership — once a week.