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Services / Agentic AIAgentic AI

Give agents boundaries before autonomy.

SBL designs agentic AI for workflows where software can plan, use tools, check data, create updates, and escalate to people. The goal is not unchecked autonomy. The goal is bounded action with permissions, approval gates, logs, and recovery paths.

Book an agentic workflow review →
01 Position

What decisions can an agent take safely, and where must a human remain in the loop Agentic AI delivery.

Bounded autonomyEvery agent has a clear goal, allowed tools, permissions, stop conditions, and escalation rules.
Tool disciplineAgents interact with systems through controlled interfaces, not broad access to business-critical platforms.
Observable actionPlans, tool calls, approvals, failures, and output changes are logged for review.
Operational fitAgents are designed around real handoffs, exception paths, and ownership after launch.
02 Capabilities

Agentic AI capabilities. Built for production.

What decisions can an agent take safely, and where must a human remain in the loop?

Capability 01
Agent workflow design
Map tasks, goals, tool access, approval points, memory, and escalation logic.
Control - Tool misuse controlOutcome - production-ready delivery
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Capability 02
Tool orchestration
Connect agents to APIs, databases, workflow systems, CRMs, document stores, and internal applications.
Control - Runaway workflow controlOutcome - production-ready delivery
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Capability 03
Human-in-the-loop control
Add review steps for high-risk actions, ambiguous outputs, and customer-facing decisions.
Control - Bad action controlOutcome - production-ready delivery
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Capability 04
Agent memory and context
Maintain useful context without exposing sensitive data or creating unmanaged state.
Control - Memory risk controlOutcome - production-ready delivery
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Capability 05
Monitoring and audit
Track tool calls, outcomes, exceptions, costs, and model behavior over time.
Control - Accountability controlOutcome - production-ready delivery
→

Production controls include tool misuse control, runaway workflow control, bad action control.

Book an agentic workflow review →
03 Stack and integration

Built around your operating stack.

LangGraph, LangChain, OpenAI, Anthropic, Azure OpenAI, Python, FastAPI, vector databases, workflow engines, event queues, REST APIs, Microsoft Graph, Salesforce, ServiceNow, SAP, Dynamics, SharePoint, databases, and cloud-native observability tools.

Stack spine

Built around your environment.

LangGraph, LangChain, OpenAI, Anthropic, Azure OpenAI, Python, FastAPI, vector databases, workflow engines, event queues, REST APIs, Microsoft Graph, Salesforce, ServiceNow, SA.

API
Integration
Cloud
Deployment
Ops
Support
Stack 01

LangGraph

Core delivery surface.

Stack 02

LangChain

Integration option.

Stack 03

OpenAI

Integration option.

Stack 04

Anthropic

Integration option.

Stack 05

Azure OpenAI

Integration option.

Stack 06

Python & PyTorch

Integration option.

Stack CTA

Discuss your stack

→
04 Industry applications

Applied where
the work happens.

The same service takes different shapes depending on data sensitivity, operating risk and the systems already in place.

B / 01BFSIclaims triage, evidence gathering, case routing, internal policy lookup, exception escalation.→H / 02Healthcareprior-authorization support, documentation follow-up, intake triage, operational task routing.→E / 03Energy and utilitiesfield-service follow-up, compliance task assembly, asset-record updates.→M / 04Manufacturingmaintenance workflow support, quality-exception routing, supplier follow-up.→E / 05Educationstudent-service triage, administrative routing, knowledge-base actions.→L / 06Logistics and supply chainshipment exception handling, document follow-up, routing support.→

4,000+ projects delivered across regulated and operationally complex industries.

05 Delivery method

From decision to
production.

Each engagement moves from workflow clarity to architecture, build and operating ownership with measurable checkpoints.

Stage 01

Bound

Identify the workflow, tasks the agent may perform, prohibited actions, exception patterns, and human owners.

2 - 4 weeks
Stage 02

Instrument

Design tool access, state, memory, approvals, logging, and evaluation criteria.

3 - 6 weeks
Stage 03

Pilot

Build the agent around one workflow with sandboxed tools, dry-run testing, and supervised release.

8 - 24 weeks
Stage 04

Govern

Expand tool access only after measured performance, audit review, and operating-model approval.

Ongoing
07 Why SBL
20+yrs

SBL brings software engineering, data operations and delivery governance into one accountable team.

"They have a high level of expertise working with a range of historic documents. Since 2015, we have completed 247 projects with them."
Rose Staveley-WadhamData Operations Manager - FindMyPast
08 Engagement models

Choose the right shape for the work.

Start with a focused assessment, a defined build, a dedicated team or managed operations depending on risk, scope and ownership.

01

Agent readiness sprint

Best for deciding where agents are safe and useful.

Best for deciding where agents are safe and useful.
02

Controlled agent pilot

Best for one bounded workflow with tool access and review gates.

Best for one bounded workflow with tool access and review gates.
03

Agent platform team

Best for shared orchestration, observability, and governance across multiple agents.

Best for shared orchestration, observability, and governance across multiple agents.
04

Managed agent operations

Best for production agents that need monitoring, evaluation, and change control.

Best for production agents that need monitoring, evaluation, and change control.
09 Contact

Start with the action you want to automate.

Tell us what the agent should do, which systems it must touch, and what it must never do without approval.

Reply within one business dayNDA available before technical discussionsSenior delivery input from the first callClear recommendation, whether we work together or not