AI with no company context
An isolated AI doesn't know your processes, customers, contracts or business rules. It answers from generic training, not from your reality.
AI agents that work
inside your operation. They don't just chat.
We build smart agents wired into your data, documents and systems to automate support, lookups, analysis and operational tasks, with security, audit and real business context.
The problem
Your company has already tried AI, and it didn't become a result.
AI that chats but doesn't execute
Without access to systems, it becomes a pretty chat. It can't look up real data, move information between tools, or finish a task end-to-end.
AI without control or audit
Right today, hallucinating tomorrow. Without quality measurement, clear permissions and a record of what was done, AI becomes risk instead of gain.
What an agent does
A Steply agent can act on your operation like this:
Answers from your company's own documents
Trained on your manuals, contracts, policies and processes. Cuts repeated questions and standardizes answers.
Looks up internal systems safely
Accesses CRM, ERP, database and spreadsheets with controlled permissions. Only returns what the user is allowed to see.
Executes tasks and triggers processes
Creates records, sends notifications, classifies requests and moves information between systems. Critical actions go through human approval.
Generates reports and analysis on demand
Summaries, comparisons, KPIs and alerts from internal data. In natural language, with sources and citations.
Helps teams with repetitive tasks
Quotes, proposals, triage, classification, checks and reports stop being done by hand.
Suggests next steps
Reads context and proposes actions: prioritize a ticket, adjust a price, flag a bottleneck. Always with an auditable rationale.
Where it creates the most value
Cases where an agent pays for itself fast.
Customer support agent
Trained on your knowledge base and procedures. Answers customers, guides agents and cuts repeated questions.
"Customer asked about return window for product X. What's the current rule?"
Internal document lookup agent
Looks up contracts, manuals, policies and procedures. Your team finds the information in seconds, with source and citation.
"Where is the annual price-adjustment rule described in Enterprise contracts?"
Sales-team support agent
Qualifies leads, answers technical questions, organizes proposals and helps sales reps save time in the pipeline.
"Draft a proposal for an industry-X client with volume Y. Use the standard template."
Management & operations agent
Queries data, raises alerts, tracks KPIs and turns scattered data into fast answers, summaries and reports.
"Which branches missed target last week? Summarize the reasons based on manager notes."
Steply premium vs generic solution
Why this isn't the same chatbot you already tried.
DIYSteply Premium
✕Generic chat with no company context✓Agent trained on your documents and processes
✕Wide-open access, no control✓Permissions per user, per team and per action type
✕No record of what was answered✓Full audit: who asked, what was done, with which source
✕AI cost with no limit and no visibility✓Limit per team, consumption alert and usage report
✕Legacy systems stay out of reach✓Safe bridges for legacy systems, no rewrite required
Security
How Steply defines "secure agent".
Security isn't an end-of-project item, it's layered architecture: infrastructure, system access, user input, agent output, scope and automation. Each layer is written, versioned and tested.
Runs in your company's environment, on your controls
- Deploy on your cloud provider or on-prem, including locally hosted models when compliance requires zero data exfiltration
- Passwords and keys stored in a vault, never in code
- Restricted network: the agent only talks to explicitly authorized systems
- Immutable log: every interaction is recorded with date, author, action and response
The agent can only do what it needs to
- Every tool has clear input/output rules, the agent never runs arbitrary commands
- Least privilege: the agent only gets the minimum access needed for the mission
- Read and write permissions are separate; data-changing actions can require human confirmation
- Every call gets a unique identifier, any action can be reconstructed in audit
What enters the agent goes through filters
- Clear separation between system instruction and user message, no naive concatenation
- Detection of attempts to manipulate the agent (keywords, hidden instructions in files)
- Per-person and per-team usage limits, automatic blocking on abuse
- Sensitive-data filter (SSN, email, phone, card) before information reaches the model
What leaves the agent is validated
- The answer goes through a format validator, if it's off-spec, it's retried
- Sensitive-data filter also on output, before reaching the user or being logged
- Toxicity and safety classifiers block or flag answers for review
- Destructive actions (delete, refund, external email) always go through a human
The agent knows what it can and cannot do
- The agent's scope is documented and reviewed, it's a contract, not a suggestion
- When there are multiple clients or units, each has a separate area, the agent never crosses data
- Document search respects user permission, if they can't see it, the agent doesn't retrieve it
- For sensitive tasks (financial, compliance), the agent can run on a local model, never leaving the network
Automated flows, not loose webhooks
- Versioned and reviewed flows, every change is recorded
- Credentials in an external vault, separate from the automation platform
- Every AI step goes through the same controls as the agent: validation, retry, failure queue
- Webhooks with signature, IP allowlist and replay protection
Compliance-ready: LGPD, GDPR and SOC2-ready structure when the client needs certification.
Why the agent costs what it costs
Transparency: where your investment goes.
The specialist agent is premium because it packs a full team into a fixed scope. Here's what's in the price, and what you won't pay later.
AI specialist + developer + ops owner + architect + reviewer. Cross-functional work packaged into a single delivery.
Living set of real cases that measures agent quality. Runs automatically on every change. Keeps growing after delivery.
All set up in your environment: system connections, credential vault, network policy and permissions, all documented and versioned.
Cost, quality, response time and anomaly alerts, visible on a dashboard from day one, no extra setup needed.
Sensitive-data filter, manipulation protection, format validation and human approval on critical actions. Audited and tested.
After delivery, 90 days tracking real usage, tuning precision, cost and integrations as per the agreed scope.
What your company saves by going with Steply
- 2 specialists + 1 internal dev × 6 months$ 48-76k in hiring + onboarding
- AI, monitoring and infrastructure tooling+ $ 6-16k/yr in licenses and infra
- Time to productionSteply: 4-8 weeks · In-house: 4-8 months
Typical case: 3-6 month payback for support or document agents, 6-12 months for ops automation. In the diagnosis we run the math for your specific case.
Pricing
Two paths: entry door and full production.
Charged per project, not per month. Range varies with scope, integrations and service-level requirements.
Entry
Agent Lite
For companies that want to test a real agent without committing the whole roadmap.
From $ 990Range: $ 990 - $ 3.6k per agent
- ✓Short diagnosis (2-3 days) and agent scope
- ✓Agent connected to 1 data source, with 3-5 tools
- ✓Initial test base (~50 cases)
- ✓Basic monitoring: usage and cost per interaction
- ✓Essential controls: validation and sensitive-data filter
- ✓Deployment in a test environment in your provider
- ✓Usage manual and handover session (2h)
- ✓30 days of technical support
PremiumPremium
Specialist Agent
For teams that want an agent that decides, not just chats.
From $ 15kRange: $ 15k - $ 55k per project
- ✓Diagnosis + agent scope in 1 sprint
- ✓Cross-functional team (AI specialist + dev + ops)
- ✓Integration with multiple systems and data sources
- ✓Models chosen per task, with local option for sensitive data
- ✓Automated test base (~300 cases) revised on every change
- ✓Full monitoring: usage, cost, quality and anomaly
- ✓Controls in 4 layers (input, output, scope, actions)
- ✓Immutable audit log
- ✓Usage manual + structured technical handover
- ✓90 days of follow-up with adjustments included
Agent FAQ
Questions decision-makers usually ask.
How long until the agent is live?
It depends on the scope. Classic cases (1 data source, 3-5 tools, medium test base): 4 to 8 weeks. Cases with legacy integration or heavy compliance requirements can reach 12-16 weeks. The diagnosis sets the timeline clearly.
Where do sensitive data live?
In your company's environment, not ours. Everything runs in your cloud or on-prem. When compliance requires zero data exfiltration, we use AI models running locally.
Do you work with legacy systems?
Yes. This includes mainframe, systems in old languages (COBOL, Delphi, VB6, Clipper) and internal platforms without documentation. We build a safe bridge, no need to rewrite everything at once.
How do you prevent the AI from "making up" answers?
Four control layers: document search only brings real and auditable information, answers are measured against pre-validated cases, format is validated before reaching the user, and critical actions always go through a human. Tests run automatically on every change.
Will the agent become a Steply dependency?
No. The code lives in your repo, with usage manual, direct access to settings and dashboards. Your internal team can fully take it over, we do a structured technical handover at the end.
Does the agent integrate with my ERP, CRM or database?
Yes. We work with systems like SAP, Oracle, Salesforce, HubSpot, BigQuery, Snowflake, Postgres, MongoDB, Stripe, Jira, Linear, Notion and internal platforms. Integrations are audited and respect existing permissions.
Got a use case in mind?
Tell us in the diagnosis. In 5 days we send back an honest analysis: is an agent worth it for this case? What scope? What expected return?
