AI Automation & Agents
Custom AI agents and process automations that reduce manual ops and scale output.
An honest read on the work
No marketing voice. A direct explanation of what the engagement actually covers and what it does not.
AI Automation and Agents is about replacing the operational glue work that drains your team — research, reporting, triage, review, follow-up, data entry, multi-tool reconciliation — with software that runs reliably without supervision. We design and build agentic systems that combine LLM reasoning, deterministic tools, structured data, and human-in-the-loop checkpoints so the automation behaves predictably under real conditions.
This service is the right fit when you can describe a workflow that a smart junior does today, where the steps are stable but the inputs are varied and unstructured. That covers a wide surface: lead enrichment and routing, contract review and clause extraction, compliance checks, ticket triage and resolution, internal research and competitive monitoring, financial reconciliation, document-driven approvals, and multi-channel campaign orchestration. If a process needs a person mostly for judgment that can be specified, we can usually automate eighty percent of it and route the rest to a reviewer.
The SoftUs difference: we build agents like software, not demos. That means typed inputs and outputs at every step, retries with backoff, idempotency, audit logs the compliance team can read, and a runtime that does not silently fail when a tool returns an unexpected payload. We avoid one-shot mega-prompts and prefer composed graphs of small, testable steps. Every agent ships with an evaluation suite, a kill switch, and a dashboard so you can see what it did, why, and what it cost.
We integrate with the tools you already pay for — Salesforce, HubSpot, Slack, Jira, Notion, Zendesk, the major email and calendar providers, your databases, your warehouse, and any internal API. The agent runs in your cloud, against your data, with credentials you control. You leave with a system you can hand to operations rather than one that requires an engineer babysitting it.
Four situations this service fits
If you recognize yourself in one of these, the engagement will move quickly. If not, we will tell you in week one.
Ops team eliminating internal busywork
You have a team spending hours daily on copy-paste between tools, lookups, triage, and follow-ups. We replace the workflow with an agent and keep humans on the judgment calls that matter.
Sales or RevOps team needing scale
Your inbound or outbound motion is bottlenecked on enrichment, qualification, and routing. We deploy agents that enrich, score, and route every lead within minutes, integrated with your CRM and sequencer.
Compliance or legal team buried in document review
You review hundreds of contracts, policies, or filings monthly. We build an extraction and review agent that pulls clauses, flags risk, and produces a human-ready summary for your reviewer.
Support team scaling without headcount
Ticket volume is rising and headcount is not. We deploy a tier-zero agent that resolves common tickets end-to-end and a tier-one agent that drafts responses for your humans to approve.
Five phases, end to end
The same shape every engagement runs in. Scoped weekly, demoed weekly, with a written deliverable at the end of every phase.
- Phase 01
Discovery & Scoping
1 weekWe shadow the current workflow, map the decision points, identify the high-volume repeatable steps, and define the success metric — usually time saved per task, throughput, or error rate against a human baseline.
- Workflow map with decision points
- Baseline throughput and error metrics
- Automation scope and exclusion list
- Human-in-the-loop policy
- Phase 02
Data & Architecture
1 to 2 weeksWe design the agent graph, define typed schemas at every step, build the tool adapters to your systems of record, and stand up the eval harness against a representative sample of real workflow inputs.
- Agent graph and step schemas
- Tool adapters for required systems
- Eval set drawn from real inputs
- Audit and observability scaffold
- Phase 03
Build & Iterate
3 to 5 weeksWe build the agent step by step, score each step in isolation, and tune the overall graph against the end-to-end metric. We run shadow mode — the agent runs alongside humans without acting — until accuracy clears the bar.
- Working agent in shadow mode
- Per-step quality scores
- Cost-per-task report
- Error handling and retry logic
- Phase 04
Validate & Harden
1 to 2 weeksWe compare the agent against the human baseline on a held-out sample, run adversarial inputs, verify idempotency and audit trail completeness, and define the human-in-the-loop thresholds for production.
- Agent versus human comparison
- Audit-log completeness check
- Kill-switch and override flow
- Human-review threshold policy
- Phase 05
Deploy & Handoff
1 weekWe move from shadow to live with a gradual rollout, monitor outcomes against the baseline, and hand off the operations dashboard. Your team can pause, override, or retrain the agent without engineering involvement.
- Phased production rollout
- Operations dashboard
- Pause and override controls
- Operations team training
Tangible artifacts, not slide decks
At handoff, you receive a working system plus the documentation, dashboards, and runbooks needed to operate it without us.
The full AI/ML stack, end to end
From data ingestion to model training to vector retrieval to evaluation, we work across the tools production AI teams actually rely on. Reliable, well understood, and easy to hand off.
Languages
Agent Frameworks
Workflow & Orchestration
LLMs & Tooling
Data & State
Observability & Eval
Three ways to work with us
Pick the shape that matches your stage. We will tell you honestly if a different model would serve you better.
Automation PoC
A four-to-six week build automating one workflow end to end, with a measured comparison against the human baseline before going live.
Teams validating that a specific workflow is automatable before committing to a wider rollout.
Embedded Pod
A SoftUs pod working alongside your ops team for a quarter, delivering and tuning multiple agents on a prioritized backlog.
Operations-heavy teams with a backlog of repeatable workflows ripe for automation.
Full-build retainer
We own the agent fleet — build, monitor, tune, expand — under a monthly retainer with quarterly roadmap reviews.
Companies running multiple agents in production without an in-house AI engineering team.
What you will gain
Concrete outcomes from our engagement — measurable impact you can track from day one.
40% cost savings by reducing repetitive manual work
Faster research and reporting by 70%
Reliable automation running 24/7 without errors
Who we build for
We work across industries where data, AI, and automation unlock real competitive advantage.
SaaS
Automated reporting and analytics
Finance
Regulatory compliance checks and audits
Healthcare
Patient data processing and scheduling
LegalTech
Contract review and clause extraction
Case studies
Examples of how we deliver under real constraints — timelines, data quality, and production requirements.
AI-Powered Marketing Automation Platform
Non-technical marketing teams struggled with fragmented tools, slow campaign setup, and inconsistent targeting across channels.
Built a multi-agent platform that automates campaign creation, audience segmentation, and omnichannel deployment — reducing setup time from days to hours.
Automated Loan Processing Platform
Loan approvals took 14 days due to manual checks, document extraction, and slow credit scoring processes.
Deployed an AI platform that extracts applicant data via OCR, runs credit scoring models, and generates underwriting recommendations in under 48 hours.
The honest answers
Direct responses to what you would ask on a first scoping call. If your question is not here, send it on the contact form and we will answer in writing within a working day.
How long does a typical engagement take?
A first agent in production usually takes six to eight weeks including shadow-mode validation. Subsequent agents are faster because the infra and observability are already in place. Expect two to three weeks for agent number two.
Who owns the IP, prompts, and tool adapters?
You do. Code, prompts, agent graphs, adapters, eval sets, and audit logs are yours. We assign IP at the contract level and remove our access at handoff.
Do you sign a DPA and are you SOC 2 friendly?
Yes. We sign DPAs as standard, run agents inside your cloud accounts, and have shipped automation inside SOC 2 and HIPAA boundaries. Audit logs are designed for compliance review from day one.
Can you integrate with our existing tools?
Yes. We have built adapters for Salesforce, HubSpot, Zendesk, Slack, Jira, Notion, Google Workspace, Microsoft 365, the major email and calendar providers, and most databases and warehouses. Custom adapters are a normal part of scope.
What happens after go-live — do you provide support?
Every agent ships with a runbook and an operations dashboard. After handoff, you can run it in-house, keep us on retainer for tuning, or call us when something upstream changes — a new tool version, a schema change, a regulatory update.
How do you price?
Fixed-scope PoCs are flat-fee. Production builds are quoted by phase with milestones tied to shadow-mode accuracy and rollout readiness. Token, infra, and tool costs run on your accounts so the unit economics are transparent.
What if the agent makes a mistake?
Every agent has confidence-thresholded routing to a human reviewer, an audit log of every action, a kill switch, and idempotent steps so reruns do not double-charge or double-send. We design for graceful failure, not perfect autonomy.
Can you start from a vague problem or do we need a spec first?
Vague is fine. Week one is workflow shadowing — we sit with the team that does the work today, watch how decisions get made, and produce the spec. Then we scope.
Adjacent work we do
Engagements that often run alongside this one.
Bring this work in-house, fast
A thirty-minute scope call gets you a written plan and a fixed quote. No slide decks, no follow-up cycle.
Have an AI idea, messy workflow, or product vision? Let's make it buildable.
Bring the problem. We'll help shape the product, define the architecture, and show the fastest path to a serious first version.
A practical first roadmap in the discovery call
Architecture, timeline, and delivery options in plain English
Security, scalability, and reliability discussed upfront
Model registry
softus-rag-v4.2
187ms
Latency
128k
Context
$0.004
Cost / req
Evaluation suite
Deploy pipeline
prod / canary 25% — healthy