Operations and business leaders
Processes that finish without chasing.
Capability
Agentic Process Automation
Agents that complete multi-step back-office work inside your systems.
Straight-through case completionCycle time per caseException and escalation rateCost per transaction
The service at a glance
The problem, our work, your result
- Business problem
Processes cross many systems, so automation stops at the first exception.
Classic automation handles only the happy path; real work needs judgement, lookups and decisions between steps.
- What we do
We build AI agents that run end-to-end processes: reading requests, checking systems, making bounded decisions, acting, and escalating to people with reasons.
- What you receive
- End-to-end process agents
- Bounded decision rules
- Human escalation paths
- Process performance analytics
Who it is for
Built for the people who own the decision
Process owners
Exceptions handled, not stuck.
CFO and finance
Lower cost per transaction.
Risk, compliance and security
Every action logged and reversible.
The goal: an AI-ready organisation
Where this service moves you
Data readyThis service
Connected, clean, governed and allowed for AI use.
KPIs readyThis service
Agreed measures, one definition each, a named owner.
Organisation readyThis service
Roles, decision rights and skills to adopt AI safely.
=AI that reaches production and creates value
Approach
How we work with you
- 01
Map
Document the real process and exceptions.
- 02
Bound
Define what the agent may decide.
- 03
Build
Connect systems and guardrails.
- 04
Supervise
Monitor, evaluate and adjust.
Engagement options
Start where you are
Process audit
Which processes suit agents.
First agent
One process automated end to end.
Agent portfolio
Many processes, centrally governed.
Scope
What is in, what is not
Included
- Agent design and build
- System integration
- Guardrails and escalation
- Evaluation and monitoring
Handled separately
- Core system replacement
- Organisation restructuring
Bilytica frameworks behind this service
Our own methods, not a generic playbook
AGENT
All Bilytica frameworksAgent Operations Framework
Autonomy tiers, tool boundaries and human checkpoints, so agents can act without becoming a liability.
See the frameworkTRUSTAI Assurance Framework
One control set that answers NIST, ISO 42001, the EU AI Act and the Saudi regulators at once.
See the frameworkIn short
What this actually is
Process-level automation where an agent plans, calls tools, reads and writes to enterprise systems and escalates when it is unsure, for reconciliation, onboarding, procurement, claims triage, and the long tail of exceptions that classic RPA scripts could never hold. Each agent has a defined scope, a permission set and an approval gate.
Key points
What matters before you buy
- 01
Scope beats ambition
A narrow agent with five tools and a clear stop condition ships; a general 'do the back office' agent does not.
- 02
Permissions are the security model
Each agent gets its own service identity and least-privilege scope, so its blast radius is knowable.
- 03
Exceptions are the point
Classic automation already handles the clean 70%; agents earn their keep on the messy remainder.
- 04
Measure completion, not activity
Cases closed without human touch, at the error rate your controls accept.
Delivery
How we build it
Foundation check
Before any buildWe inspect the systems, the data behind them and the quality of the records this capability will depend on, then write down what has to be fixed before anything is built.
Narrow first release
First releaseOne workflow, one team, real traffic, measured against the baseline we captured before we started.
Controls and evaluation
Runs in parallelGuardrails, approval gates, evaluation sets, logging and the evidence pack your auditor and your regulator will ask for.
Scale and hand over
After sign-offAdditional workflows, sites or languages, then runbooks and training so your team can operate it without us.
Data foundation
What has to be true in your data first
Great AI cannot hide bad data. These are the conditions this capability depends on, we fix them as part of delivery, not after go-live.
- A documented process with its real exception paths, not the idealised diagram.
- APIs or stable interfaces for every system the agent must touch.
- Service accounts with least-privilege scopes.
- A ground-truth set of completed cases to evaluate against.
Controls
Guardrails we put around it
A human owns every consequential decision
Agents draft, route and execute reversible steps. Anything that moves money, changes a record of consequence or affects a person's rights stops at a named human approver with the reasoning attached.
Every action is logged and replayable
Inputs, retrieved context, model version, output and the human decision are written to an immutable log, so an auditor can reconstruct any single interaction months later.
Data stays where your regulator requires
In-country, in-region or on-premise deployment, with the model portfolio right-sized to the workload instead of routing everything to a frontier endpoint abroad.
Accuracy is monitored, not assumed
A held-out evaluation set runs on every model or prompt change, with drift alerts and a documented rollback path when quality moves.
Fit
Systems it plugs into, and what it moves
Integrations
SAPOracleMicrosoft Dynamics 365ServiceNowUiPath / Power AutomateSalesforceInternal APIs
KPIs it moves
- • Straight-through case completion
- • Cycle time per case
- • Exception and escalation rate
- • Cost per transaction
- • Control breaches, target zero