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Intake, qualification, drafting and CRM update are separate components coordinated under one process record with one approval gate. Needs: the handoffs between teams and the systems involved.
AI Orchestration & Integrations
AI & Digital Orchestration
REIT Limited, a Bangladesh-based AI services and technical-delivery company, designs the coordination layer that makes several agents, workflows and systems behave as one accountable process.
What it is
AI orchestration is the coordination of several AI agents, models, workflows and business systems as one managed process. The design specifies what runs next, what information is shared between steps, where a person must approve, and how a failure is detected and recovered, so the whole process can be seen and owned.
What does AI orchestration fix that single automations cannot?
Separate automations do not know about each other. Orchestration gives them one shared record of each case, typed hand-offs, permissions, monitoring and recovery, so an end-to-end process has a visible state and a named owner.
A business that has built a few automations often finds they do not add up to a process. One workflow hands work to another with no shared record. An agent acts on information another step has already changed. When something fails, nobody can see where, and costs are scattered across tools.
Orchestration treats the end-to-end process as the unit of design. A single automation does not become orchestration because it calls a model; the need arises when several parts must share state and fail safely together.
Where does AI & Digital Orchestration fit?
Four situations where this service fits, with what each needs from you.
Document processing chain
Extraction, classification, checking and filing agents pass work in sequence, with a reviewer for low-confidence items. Needs: sample documents and acceptance thresholds.
Support operations
A triage agent, a knowledge assistant and a ticketing workflow share context so a customer is not asked twice. Needs: ticketing access and knowledge sources.
Connecting existing systems
CRM, helpdesk, documents and messaging are connected through a controlled layer with permissions and logging. Needs: API access and an owner for each system.
What does REIT Limited deliver?
A designed, built, tested and documented engagement with written acceptance checks, an operating guide and a handover. This section lists what is included, what is optional, what is excluded and what stays with you.
What REIT Limited delivers
- A map of triggers, tools, outputs, owners and escalation points
- Task routing and sequencing across agents, workflows and people
- Shared process state, so each step sees the current facts
- Model selection for each step, with the reason recorded
- Handoffs, dependency management and approval gates
- Centralised execution visibility across the whole process
- Retry and recovery rules for tool failure and invalid output
- Cost controls and a named operating owner
Optional additions
- Connections to further business systems
- Governance records: prompt and model versions, permissions and change history
- Ongoing operation through AI System Assurance & Support
Not included
- Systems that expose no API or other agreed connection method
- Replacement of the business systems being coordinated
- Vendor and model usage charges
Stays with you
- Ownership of each connected system and its data
- Approval policy for sensitive and customer-facing actions
- The named operating owner's authority to stop the process
| Capability | What it covers | Typical tools and connections |
|---|---|---|
| Workflow orchestration | The sequence of work across people, AI tools, APIs, business systems and approval stages | Orchestration service, process map |
| Multi-agent coordination | Specialised agents for research, extraction, classification, drafting, checks and reporting, each with one role | Agent roles, typed hand-offs |
| Shared state | One record of where each case is, what has been done and what it waits for | State store, case dashboard |
| Systems integration | CRM, helpdesk, ERP, email, knowledge bases, document stores and internal tools connected with controlled data flows | APIs, webhooks, connectors |
| Reusable integration layer | Connectors, transformations and logging built once and reused by later AI projects | API connectors, event triggers |
| Governance and controls | Prompt versions, model choices, permissions, escalation rules and change history | Configuration repository, change log |
| Monitoring and recovery | Success rates, API failures, cost anomalies, retries and incident records | Execution monitor, alerts, cost report |
| Legacy modernisation | An old system brought into the process through an interface, without replacing it at once | API wrapper, staged rollout, rollback plan |
Supported systems and connections
- CRM
- Helpdesk
- ERP
- Knowledge bases
- Document stores
- E-signature
- Billing systems
- Messaging tools
- Internal applications
A connection is confirmed in the assessment, after checking the interface, permissions and vendor limits of each system.
How does the process work?
The stages are colour-coded the same way across this website: input, processing, human approval, outcome.
- InputProcess startsA trigger creates one shared process record.
- ProcessingRoute the taskThe controller decides which component acts next.
- ProcessingComponents actAgents and workflows work from the shared state.
- Human approvalApproval gateDefined actions wait for a named person.
- OutcomeVisible resultOutcome, cost and each step appear in one view.
What result can it produce?
One engagement, with the measures agreed before the pilot and reported after launch.
Case studySample case study
Client onboarding coordinated across five systems
Quillhaven Legal Services · Legal services, Canada
- 2 daysMedian onboarding timelower, was 9 days
- 4%Matters stalled over 3 dayslower, was 31%
- 2Manual hand-off emails per matterlower, was 14
The problem
Opening a new client matter touched the CRM, conflict-check database, document system, billing and e-signature. Each step was started by email, and matters stalled between teams.
What was built
- One orchestration layer that holds the state of each matter from enquiry to signed engagement letter
- Three specialised steps (conflict search summary, engagement-letter draft, billing set-up) with typed hand-offs
- A dashboard showing every open matter, its current owner and how long it has waited
Where a person approves
A partner approves the conflict summary and the engagement letter. Nothing is sent to a client or written to billing before that approval is recorded.
The result
Median onboarding time fell from 9 working days to 2. Stalled matters, previously found by chasing email, are visible the same day.
Systems and tools
- Orchestration service with shared state
- CRM API
- Document management API
- E-signature API
- Billing system connector
- Execution log and cost monitor
Limit found
The conflict database has no write API, so the result is recorded by a person; the orchestration waits for that confirmation.
- Before launch
- After launch
- 9.5Oct
- 9Nov
- 8.5Dec
- 4Jan
- 2.5Feb
- 2Mar
View data table
| Period | Value |
|---|---|
| Oct | 9.5 |
| Nov | 9 |
| Dec | 8.5 |
| Jan | 4 |
| Feb | 2.5 |
| Mar | 2 |
Sample data
- Sector
- Legal services
- Country
- Canada
- Size
- 60 staff
- Timeline
- Pilot 4 weeks, implementation 10 weeks
What does the published evidence say?
Figures from named surveys and official statistics, each with its source.
15%
of surveyed US organisations have scaled orchestrated, cross-functional multi-agent adoption, although 42% have tested or deployed AI agents.
Deloitte, 12 August 2026Survey of 501 US leaders, April to June 2026
22%
of organisations have successfully scaled AI across multiple business units or adopted an AI-first approach.
Gartner, 1 September 2026Survey of 1,303 organisations with at least USD 50 million revenue, January to April 2026
21%
of respondents say their organisations have a mature governance model in place for agentic AI.
Deloitte Insights, 24 April 2026Survey of 3,235 leaders in 24 countries
How is quality controlled?
Through acceptance checks agreed before the build, named approvers for sensitive actions, access limited to what you grant, monitoring with alerts, written recovery steps and a named owner after handover.
- Execution visibility
- One place shows which runs succeeded, failed or are waiting, and why.
- Recovery
- Retries, fallbacks and manual recovery steps are defined for each failure type.
- Permissions
- Each agent and workflow is limited to a specified role and tool set.
- Version control
- Prompts, models and rules are versioned so a change can be traced and reversed.
- Cost visibility
- Model and tool usage is recorded per process so anomalies are noticed.
- Ownership
- A named person owns the process and receives its alerts.
What does it cost and how do we start?
Work starts with a paid AI assessment of one process (USD 500, usually 5 working days). A scoped pilot follows (from USD 2,500), then implementation and support, each priced in a written proposal.
AI assessment
USD 500
5 working days
One process reviewed for fit, dependencies and risk.
Scoped pilot
from USD 2,500
3 to 4 weeks
One bounded use case built and tested on real cases.
Production implementation
from USD 6,000
6 to 10 weeks
The accepted pilot hardened, connected and launched.
Sample pricesPrices exclude third-party licences, model usage and taxes. The proposal sets the final price for your scope. Invoices are issued in USD; GBP, EUR and AUD are available on request.
The first step is an AI assessment of one process or one bounded task. It establishes whether the work is a sound candidate, what it depends on, and what a pilot would cover. An enquiry is a request for that conversation; it is not an appointment or an order.
Build work is quoted in the proposal that follows the assessment. Third-party licences, model usage and hosting are recurring costs and are shown separately from implementation. Ongoing support is a separate arrangement with its own scope. See How We Work for how the stages differ.
Questions buyers ask
What is AI orchestration, and when is one workflow not enough?
AI orchestration coordinates several agents, models, workflows and systems as one managed process with shared state and one view of execution. One workflow is enough when the path is known and a single tool can run it. Orchestration becomes useful when work crosses several systems or teams, when steps depend on each other's results, and when a failure in one part must be handled by the whole.
Can you connect our existing CRM, helpdesk and knowledge sources?
It depends on what each system exposes. Feasibility turns on available APIs, access permissions, data quality and vendor restrictions, which REIT Limited checks during the assessment before committing to scope. Not every application has a supported connection, and the assessment says so where that is the case.
Who is responsible when an orchestrated process fails?
The design names an operating owner who receives alerts and decides on recovery. Retry and fallback rules handle expected failures automatically; anything else stops and waits for that person. After handover, responsibility for operation sits with whoever the proposal names, which may be your team or a support arrangement.
Start with one process
Tell us the process or task you want to improve, the systems it touches and the result you need.
- Assessment before any build
- A person approves customer-facing actions
- Registered in Bangladesh, RJSC No. C-169247/2021