Softment
AIAI assistants that perform actions via APIs

Technology

Function Calling / Tools

Function Calling / Tools implementation for production software delivery with clean architecture, maintainability, and predictable rollout. Built for United States teams with Americas overlap (EST/PST-friendly).

Best For

Ideal use cases

Assistants needing controlled access to business functions

Teams automating operational workflows with AI

Products requiring safe action execution from chat interfaces

What We Build

Projects we deliver

Tool schemas and action contracts for AI assistants

Function-calling orchestration and validation layers

Permission-aware AI action execution workflows

Ecosystem

Compatible tools & integrations

Seamless Integrations

Works with your existing stack

4+ supported
Tool schema definitions
Execution routers and validators
API permission boundaries
Action logging and audit traces

Use Cases

Recommended use cases

Internal ops assistants

Customer support automation with safe actions

AI-driven workflow orchestration

Delivery

How we deliver

Tool actions are constrained by explicit validation and permissions.

Fallback paths are included when tool calls fail.

Action observability is built for auditability and troubleshooting.

FAQ

Frequently asked questions

Function calling lets models trigger predefined tools/APIs in structured ways rather than free-form responses.

We enforce schema validation, permission checks, and allowlists before executing any action.

Yes. We map business APIs into controlled tool interfaces for reliable assistant behavior.

Regional

Delivery considerations for your region

Data and risk discovery (United States)

Privacy, security, residency, and regulatory requirements differ by workflow. We document the applicable data flows, roles, retention needs, and control owners before recommending an architecture.

The resulting proposal lists the controls and evidence that are actually in scope. It is not a generic compliance, certification, or legal-assurance promise.

  • Map data sources, destinations, roles, and sensitive fields
  • Record access, retention, logging, and deletion requirements
  • Identify required security or procurement evidence before contracting
  • Use an NDA or DPA only when the parties mutually execute it

Working model (United States)

Exact live-overlap hours, response expectations, meeting windows, and escalation contacts are confirmed in the proposal for each engagement.

Written decisions, scoped milestones, and asynchronous updates reduce unnecessary meetings without implying an unagreed service level.

  • Proposal-specific overlap and meeting windows
  • Named owners for decisions and blockers
  • Written scope, assumptions, and change decisions
  • Milestone cadence agreed before kickoff

Commercial setup (United States)

The contracting entity, proposal currency, invoicing cadence, payment terms, intellectual-property terms, and required vendor documents are agreed before work begins.

The Opportunity Sprint can establish the evidence needed to scope a production pilot; it does not pre-commit either party to a rollout.

  • Contracting entity and currency confirmed in writing
  • Milestones and acceptance criteria defined in the proposal
  • Vendor-document requirements identified before signature
  • Scope changes require an explicit written decision

Delivery controls (United States)

Testing, observability, release, security, and handover controls are selected for the actual system risk rather than promised as a generic bundle.

Acceptance measures and production responsibilities are recorded before implementation so both teams know what evidence will support release.

  • Risk-based testing and acceptance measures
  • Release, rollback, and observability responsibilities
  • Security controls tied to the agreed threat model
  • Handover artifacts defined in the signed scope
Ready to start?

Want to scope this properly?

Share your requirements for United States delivery. proposal currency confirmed before contracting.

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