AI ORCHESTRATION

AI Agent Orchestration & Multi-Agent Systems

One agent is useful. A team of specialised agents, coordinated by a reliable orchestrator, runs entire processes. We build the conductor that keeps them accurate, accountable and cost-efficient.

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AI Orchestration

The orchestrator is the control plane of enterprise AI

As soon as you have more than one agent, model or tool, you need orchestration: who does what, in which order, with which data, under which policy - and what happens when a step fails. Our orchestrator layer provides routing, shared state, retries, approvals, cost budgets and a single pane of glass for every run.

What We Deliver

Capabilities included in AI Orchestration

Supervisor & router agents

Route each request to the best specialist agent or model based on intent, cost and risk.

Stateful workflows

Durable graphs with checkpoints, retries, parallel branches and long-running tasks.

Shared memory & context

Common knowledge store so agents hand over work without losing context.

Model routing & cost control

Send easy tasks to small models and hard ones to frontier models; enforce token budgets.

Human approvals

Pause, review, edit and resume runs - with role-based approvals and audit trails.

Tracing & observability

End-to-end traces, latency, cost and quality scores for every agent step.

Technology & Platforms

Tools and models we work with

LangGraphTemporalCrewAIAutoGenSemantic KernelPrefectAirflown8nKafkaRedisOpenTelemetryLangSmithLangfuseMCPA2A protocol

How We Deliver

A proven path from idea to production

Map the process

Break the business process into roles, hand-offs and decision points.

Define agents & tools

Specialist agents with scoped tools and permissions.

Build the orchestrator

Routing, state, memory, policies and failure handling.

Test at scale

Simulation, evaluation suites and chaos testing for edge cases.

Run & govern

Dashboards, cost budgets, approvals and continuous improvement.

Use Cases

Where it creates business value

Loan & KYC processing

Document, verification, risk and compliance agents coordinated end to end.

Supply chain control tower

Forecast, procurement and logistics agents negotiating exceptions.

Claims & case handling

Intake, validation, policy and payment agents with human sign-off.

Omnichannel support desk

Triage, knowledge, billing and escalation agents behind one customer thread.

Software delivery copilots

Planning, coding, testing and release agents in your DevOps pipeline.

Marketing operations

Research, content, approval and publishing agents with brand guardrails.

Commercials & Engagement Models

Flexible ways to start and scale

Pick the model that fits your stage and risk appetite. Every quote is tailored to your scope - and every cost driver is explained upfront.

FIXED SCOPE

AI Discovery Workshop

1-2 weeks. Use-case discovery, data and architecture review, ROI model and a costed roadmap.

FIXED PRICE

Proof of Concept / Pilot

3-6 weeks. A working solution on your real data with success metrics and a clear go / no-go.

MILESTONE

Fixed-Scope Project

Scoped build with milestone payments, defined deliverables and acceptance criteria.

MONTHLY

Dedicated AI Pod

A cross-functional team - AI engineer, data engineer, solution architect, QA - on a monthly retainer.

SLA

Managed AI Operations

LLMOps monitoring, evaluation, tuning, cost control and incident response under a monthly SLA.

PASS-THROUGH

Usage-Based Costs

LLM tokens, vector databases and GPU compute billed at cost, or run in your own cloud account.

PERFORMANCE

Outcome-Linked Options

For well-measured processes, part of the fee tied to agreed KPIs such as hours saved or cases resolved.

LICENCE

Product & Platform Licences

Subscription for our reusable orchestrator, RAG and MCP accelerators to cut build time.

What drives the price

Scope & number of use cases

Data readiness & quality

Number of integrations (ERP, CRM, APIs)

Model choice & token volume

Cloud, private cloud or on-prem GPUs

Security, privacy & compliance needs

Languages & channels (WhatsApp, voice, web)

Accuracy targets & human review level

Support SLA & hours of coverage

Training & change management

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FAQ

Frequently asked questions

What is an AI orchestrator?

An AI orchestrator is the control layer that coordinates multiple agents, models, tools and humans: it routes tasks, manages state and memory, enforces policy and records every step.

Do we need orchestration for a single agent?

Not always, but production agents still need state, retries, approvals and observability - which is orchestration in a lighter form.

Which standards do you support?

We support Model Context Protocol (MCP) for tools and data, plus emerging agent-to-agent protocols, so your system is not locked to one vendor.

Can we host the orchestrator ourselves?

Yes - cloud, private cloud or fully on-premise deployments are supported.