Support resolution
Agents that read a ticket, pull the right context, take the fix action and only escalate the cases that genuinely need a human.
Agents that take
real actions.
Not another chatbot. We build goal-driven agents that plan, call your tools and complete multi-step work — with approvals, stop conditions and an audit trail, so autonomy never means losing control.
Tool usereads and acts
in your systems
in your systems
Approvalshumans stay in
the loop by design
the loop by design
Traceableevery step logged
and reviewable
and reviewable
Tool & action use
Multi-step planning
Approvals & guardrails
Observable in production
What agents take on
Work that’s more than
Work that’s more than
a single answer.
Agents shine where a task has steps, tools and decisions — the multi-step work that eats a person’s afternoon.
Operations automation
Onboarding, reconciliation, updates across systems — the routine ops work that’s too fiddly for a script but perfect for an agent.
Research & analysis
Gather from many sources, cross-check, summarise and produce a decision-ready brief — with its sources shown.
Task execution
Give the agent a goal and the tools to reach it — it plans the steps, does the work and checks in where you told it to.
What’s included
The parts that make
The parts that make
an agent dependable.
Autonomy is only useful when it’s reliable and safe. We build every layer that separates a real agent from a risky demo.
01
Hands, not just a mouth
Tool & action use
Well-scoped tools that let the agent read data and take actions in your systems — each one defined, permissioned and safe.
Function callingAPI actionsScoped accessDry-run mode
02
Think before acting
Planning & reasoning
The agent breaks a goal into steps, chooses tools and adapts when something fails — instead of blindly running a fixed script.
Task planningRetriesSelf-correctionFallbacks
03
You decide the boundaries
Approvals & limits
Human-in-the-loop checkpoints, spend and rate limits and hard stop conditions on anything sensitive, so autonomy stays inside your rules.
Approval stepsRate limitsStop conditionsSandboxing
04
Remembers what matters
Memory & context
Retrieval and memory so the agent keeps the thread across steps and sessions, grounded in your data rather than starting cold each time.
RAGSession memoryStateContext windows
05
A team, when one isn’t enough
Multi-agent orchestration
Specialised agents that hand work to each other under a coordinator — for jobs too broad for a single prompt to own well.
CoordinatorSpecialistsHand-offsShared state
06
Trust you can verify
Guardrails & monitoring
Output guardrails, evaluation suites and full run tracing so you can see every decision the agent made — and prove it behaved.
GuardrailsEvalsRun tracesAlerts
How we work
From a goal
From a goal
to an agent you trust.
We earn autonomy in stages — starting supervised, proving reliability, then widening what the agent is allowed to do on its own.
Define the job
We pin down the goal, the boundaries and the definition of done — what the agent should do, what it must never do and how success is measured.
Tool design
We build the scoped tools the agent needs to read and act, each with clear inputs, permissions and safe defaults — including dry-run modes.
Planning & reasoning
We shape how the agent decomposes work, recovers from errors and knows when to ask — the difference between capable and chaotic.
Guardrails & approvals
We add the checkpoints, limits and stop conditions that keep autonomy safe, and decide together which actions need a human to sign off.
Evaluation
We build test scenarios and score the agent on them, so reliability is proven with numbers before it’s trusted with real work.
Deploy & observe
We launch supervised, watch every run, and widen the agent’s autonomy as the evidence earns it — never before.
Direct answers
Questions before
Questions before
you hand over.
Autonomy raises fair questions about trust and safety — here are straight answers to the ones we hear most.
Ask us somethingScoped tools, hard limits and stop conditions constrain what an agent can do, human approval gates sit in front of sensitive actions, and every run is traced — so nothing consequential happens without a boundary and a record.
Reliable when engineered for it. We measure agents against evaluation scenarios, start them supervised and only widen autonomy as the numbers earn it — rather than shipping hope and hoping.
Yes. Agents act through tools we build against your CRM, databases, internal APIs and third-party services — reading and acting only within the permissions you set.
As much as it earns, and no more. We often start with the agent proposing actions for approval, then let it act unattended on the low-risk paths once it’s proven — you decide the line.
It depends on the number of tools, the reliability bar and integrations. After a short discovery we give a range tied to milestones, plus the ongoing model and infrastructure costs to run it.
Contact
Let’s make the next
Let’s make the next
move count.
Tell us what you are building. We will come back within one business day with questions, not a pitch deck.